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Yongmiao Hong

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2023. "Optimal Local Model Averaging for Divergent-Dimensional Functional-Coefficient Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202309, University of Kansas, Department of Economics, revised Sep 2023.
    3. Zongwu Cai & Gunawan, 2023. "A Combination Forecast for Nonparametric Models with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202310, University of Kansas, Department of Economics, revised Sep 2023.
    4. Zhang, Xinyu & Liu, Chu-An, 2023. "Model averaging prediction by K-fold cross-validation," Journal of Econometrics, Elsevier, vol. 235(1), pages 280-301.
    5. Chen, Yi-Ting & Liu, Chu-An, 2023. "Model averaging for asymptotically optimal combined forecasts," Journal of Econometrics, Elsevier, vol. 235(2), pages 592-607.
    6. Victoria Stack & Lana L. Narine, 2022. "Sustainability at Auburn University: Assessing Rooftop Solar Energy Potential for Electricity Generation with Remote Sensing and GIS in a Southern US Campus," Sustainability, MDPI, vol. 14(2), pages 1-14, January.
    7. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    8. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.
    9. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.

  2. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.

    Cited by:

    1. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.

  3. Hong, Yongmiao & Wang, Dabin & Zhang, Xiaobo, 2005. "Identifying Threshold Effects and Typologies in Economic Growth: A Panel Approach," 2005 Annual meeting, July 24-27, Providence, RI 19163, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    Cited by:

    1. Andros Kourtellos & Chih Ming Tan & Xiaobo Zhang, 2006. "Is the Relationship Between Aid and Economic Growth Nonlinear?," Discussion Papers Series, Department of Economics, Tufts University 0614, Department of Economics, Tufts University.

  4. Jaehun Chung & Yongmiao Hong, 2004. "Are the directions of stock price changes predictable? A generalized cross-spectral approach," Econometric Society 2004 North American Winter Meetings 469, Econometric Society.

    Cited by:

    1. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.

  5. Cai, Zongwu & Hong, Yongmiao, 2003. "Nonparametric Methods in Continuous-Time Finance: A Selective Review," SFB 373 Discussion Papers 2003,15, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Bandi, Federico M. & Moloche, Guillermo, 2018. "On The Functional Estimation Of Multivariate Diffusion Processes," Econometric Theory, Cambridge University Press, vol. 34(4), pages 896-946, August.
    2. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    3. Fan, Jianqing & Fan, Yingying & Jiang, Jiancheng, 2007. "Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 618-631, June.
    4. Jianqing Fan, 2004. "A selective overview of nonparametric methods in financial econometrics," Papers math/0411034, arXiv.org.
    5. Aït-Sahalia, Yacine & Park, Joon Y., 2016. "Bandwidth selection and asymptotic properties of local nonparametric estimators in possibly nonstationary continuous-time models," Journal of Econometrics, Elsevier, vol. 192(1), pages 119-138.
    6. Jianqing Fan & Yingying Fan & Jinchi Lv, 0. "Aggregation of Nonparametric Estimators for Volatility Matrix," Journal of Financial Econometrics, Oxford University Press, vol. 5(3), pages 321-357.
    7. Chen, Song Xi & Gao, Jiti & Tang, Chenghong, 2005. "A test for model specification of diffusion processes," MPRA Paper 11976, University Library of Munich, Germany, revised Feb 2007.

  6. Hong, Yongmiao & Li, Haitao, 2002. "Nonparametric specification testing for continuous-time models with application to spot interest rates," SFB 373 Discussion Papers 2002,32, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
    2. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Paulo M. M. Rodrigues & Antonio Rubia, 2004. "On the Small Sample Properties of Dickey Fuller and Maximum Likelihood Unit Root Tests on Discrete-Sampled Short-Term Interest Rates," Econometrics 0405004, University Library of Munich, Germany.
    4. Chen, Xiaohong & Fan, Yanqin & Patton, Andrew J., 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics 24681, London School of Economics and Political Science, LSE Library.
    5. Yanqin Fan & Xiaohong Chen & Andrew Patton, 2004. "(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates," FMG Discussion Papers dp483, Financial Markets Group.
    6. N. Meddahi & C. Bontemps, 2004. "Testing Distributional Assumptions: A GMM Approach," Econometric Society 2004 North American Winter Meetings 487, Econometric Society.
    7. Jean-David Fermanian, 2003. "Goodness of Fit Tests for Copulas," Working Papers 2003-34, Center for Research in Economics and Statistics.
    8. Federico M. Bandi & Peter C.B. Phillips, 2005. "A Simple Approach to the Parametric Estimation of Potentially Nonstationary Diffusions," Cowles Foundation Discussion Papers 1522, Cowles Foundation for Research in Economics, Yale University.
    9. Kristensen, Dennis, 2004. "A semiparametric single-factor model of the term structure," LSE Research Online Documents on Economics 24741, London School of Economics and Political Science, LSE Library.
    10. Valentina Corradi & Norman R. Swanson, 2003. "Bootstrap Specification Tests for Diffusion Processes," Departmental Working Papers 200321, Rutgers University, Department of Economics.
    11. Fuchun Li, 2005. "Testing the Parametric Specification of the Diffusion Function in a Diffusion Process," Staff Working Papers 05-35, Bank of Canada.
    12. Dennis Kristensen, 2007. "Nonparametric Estimation and Misspecification Testing of Diffusion Models," CREATES Research Papers 2007-01, Department of Economics and Business Economics, Aarhus University.
    13. Hamilton, James D. & Wu, Jing Cynthia, 2014. "Testable implications of affine term structure models," Journal of Econometrics, Elsevier, vol. 178(P2), pages 231-242.
    14. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
    15. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    16. Xiaohong Chen & Yanqin Fan, 2002. "Evaluating Density Forecasts via the Copula Approach," Vanderbilt University Department of Economics Working Papers 0225, Vanderbilt University Department of Economics, revised Sep 2003.
    17. Egorov, Alexei V. & Li, Haitao & Xu, Yuewu, 2003. "Maximum likelihood estimation of time-inhomogeneous diffusions," Journal of Econometrics, Elsevier, vol. 114(1), pages 107-139, May.
    18. Durham, Garland B., 2007. "SV mixture models with application to S&P 500 index returns," Journal of Financial Economics, Elsevier, vol. 85(3), pages 822-856, September.
    19. Li, Fuchun & Tkacz, Greg, 2006. "A consistent bootstrap test for conditional density functions with time-series data," Journal of Econometrics, Elsevier, vol. 133(2), pages 863-886, August.
    20. Peter C. B. Phillips & Jun Yu, 2005. "Comments on “A Selective Overview of Nonparametric Methods in Financial Econometrics” by Jianqing Fan," Working Papers 08-2005, Singapore Management University, School of Economics.

  7. Giampiero M. Gallo & Yongmiao Hong & Tae-Why Lee, 2001. "Modelling the Impact of Overnight Surprises on Intra-daily Stock Returns," Econometrics Working Papers Archive wp2001_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    2. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    3. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    4. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    5. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    6. Blanc, Pierre & Chicheportiche, Rémy & Bouchaud, Jean-Philippe, 2014. "The fine structure of volatility feedback II: Overnight and intra-day effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 58-75.
    7. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    8. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
    9. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
    10. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.

  8. Yongmiao Hong & Jin Lee, 2000. "Wavelet-based Estimation for Heteroskedasticity and Autocorrelation Consistent Variance-Covariance Matrices," Econometric Society World Congress 2000 Contributed Papers 1211, Econometric Society.

    Cited by:

    1. Sun, Yixiao & Phillips, Peter C.B. & Jin, Sainan, 2011. "Power Maximization And Size Control In Heteroskedasticity And Autocorrelation Robust Tests With Exponentiated Kernels," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1320-1368, December.
    2. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.
    3. Gencay, Ramazan & Fan, Yanqin, 2007. "Unit Root Tests with Wavelets," MPRA Paper 9832, University Library of Munich, Germany.
    4. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
    5. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    6. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2005. "Improved HAR Inference," Cowles Foundation Discussion Papers 1513, Cowles Foundation for Research in Economics, Yale University.
    7. Jin Lee, 2000. "One-Sided Testing for ARCH Effect Using Wavelets," Econometric Society World Congress 2000 Contributed Papers 1214, Econometric Society.

  9. Yongmiao Hong & Chihwa Kao, 2000. "Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models," Center for Policy Research Working Papers 32, Center for Policy Research, Maxwell School, Syracuse University.

    Cited by:

    1. Hafner, Christian, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," LIDAM Reprints ISBA 2012027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Tzagkarakis George & Dionysopoulos Thomas & Achim Alin, 2016. "Recurrence quantification analysis of denoised index returns via alpha-stable modeling of wavelet coefficients: detecting switching volatility regimes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 75-96, February.
    3. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.
    4. Antonis Michis, 2014. "Time Scale Evaluation of Economic Forecasts," Working Papers 2014-1, Central Bank of Cyprus.
    5. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    6. Li, Linyuan & Yao, Shan & Duchesne, Pierre, 2014. "On wavelet-based testing for serial correlation of unknown form using Fan’s adaptive Neyman method," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 308-327.
    7. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.
    8. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.
    9. Gencay, Ramazan & Fan, Yanqin, 2007. "Unit Root Tests with Wavelets," MPRA Paper 9832, University Library of Munich, Germany.
    10. Gonçalo Faria & Fabio Verona, 2016. "Forecasting stock market returns by summing the frequency-decomposed parts," Working Papers de Economia (Economics Working Papers) 05, Católica Porto Business School, Universidade Católica Portuguesa.
    11. Viviana Fernandez, 2004. "Time-Scale Decomposition of Price Transmission in International Markets," Documentos de Trabajo 189, Centro de Economía Aplicada, Universidad de Chile.
    12. Wu, Jianhong & Zhu, Lixing, 2011. "Testing for serial correlation and random effects in a two-way error component regression model," Economic Modelling, Elsevier, vol. 28(6), pages 2377-2386.
    13. Viviana Fernandez & Ali M. Kutan, 2005. "Do Regional Integration Agreements Increase Business-Cycle Convergence? Evidence From APEC and NAFTA," William Davidson Institute Working Papers Series wp765, William Davidson Institute at the University of Michigan.
    14. Okui, Ryo, 2009. "Testing serial correlation in fixed effects regression models based on asymptotically unbiased autocorrelation estimators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2897-2909.
    15. Yushu Li & Fredrik N. G. Andersson, 2021. "A simple wavelet-based test for serial correlation in panel data models," Empirical Economics, Springer, vol. 60(5), pages 2351-2363, May.
    16. Viviana Fernandez, 2008. "Traditional versus novel forecasting techniques: how much do we gain?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 637-648.
    17. Chen Yi-Ting & Sun Edward W. & Yu Min-Teh, 2015. "Improving model performance with the integrated wavelet denoising method," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 445-467, September.
    18. Haven, Emmanuel & Liu, Xiaoquan & Shen, Liya, 2012. "De-noising option prices with the wavelet method," European Journal of Operational Research, Elsevier, vol. 222(1), pages 104-112.
    19. Wu, Jianhong, 2020. "A joint test for serial correlation and heteroscedasticity in fixed-T panel regression models with interactive effects," Economics Letters, Elsevier, vol. 197(C).
    20. Gençay, Ramazan & Signori, Daniele, 2015. "Multi-scale tests for serial correlation," Journal of Econometrics, Elsevier, vol. 184(1), pages 62-80.
    21. Fernandez, Viviana, 2006. "The CAPM and value at risk at different time-scales," International Review of Financial Analysis, Elsevier, vol. 15(3), pages 203-219.
    22. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
    23. Yi-Ting Chen & Edward W. Sun & Min-Teh Yu, 2018. "Risk Assessment with Wavelet Feature Engineering for High-Frequency Portfolio Trading," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 653-684, August.
    24. Thomas Conlon & John Cotter & Ramazan Gençay, 2015. "Long-run international diversification," Working Papers 201502, Geary Institute, University College Dublin.
    25. Stelios Bekiros, 2014. "Timescale Analysis with an Entropy-Based Shift-Invariant Discrete Wavelet Transform," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 231-251, August.
    26. Zhou, Yong & Wan, Alan T.K. & Xie, Shangyu & Wang, Xiaojing, 2010. "Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 183-201, November.
    27. Meinl Thomas & Sun Edward W., 2012. "A Nonlinear Filtering Algorithm based on Wavelet Transforms for High-Frequency Financial Data Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-24, September.
    28. Liu, Xiaoquan & Cao, Yi & Ma, Chenghu & Shen, Liya, 2019. "Wavelet-based option pricing: An empirical study," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1132-1142.
    29. Conlon, Thomas & Cotter, John & Gençay, Ramazan, 2018. "Long-run wavelet-based correlation for financial time series," European Journal of Operational Research, Elsevier, vol. 271(2), pages 676-696.
    30. Sun, Edward W. & Chen, Yi-Ting & Yu, Min-Teh, 2015. "Generalized optimal wavelet decomposing algorithm for big financial data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 194-214.
    31. Fernandez, Viviana, 2006. "Does domestic cooperation lead to business-cycle convergence and financial linkages?," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(3), pages 369-396, July.
    32. Li, Linyuan & Duchesne, Pierre & Liou, Chu Pheuil, 2021. "On diagnostic checking in ARMA models with conditionally heteroscedastic martingale difference using wavelet methods," Econometrics and Statistics, Elsevier, vol. 19(C), pages 169-187.

  10. White, Halbert & Hong, Yongmiao, 1999. "M-Testing Using Finite and Infinite Dimensional Parameter Estimators," University of California at San Diego, Economics Working Paper Series qt9qz123ng, Department of Economics, UC San Diego.

    Cited by:

    1. Aït-Sahalia, Yacine. & Bickel, Peter J. & Stoker, Thomas M., 1994. "Goodness-of-fit tests for regression using kernel methods," Working papers 3747-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Natércia Fortuna, 2004. "Local rank tests in a multivariate nonparametric relationship," FEP Working Papers 137, Universidade do Porto, Faculdade de Economia do Porto.

  11. Hong, Yongmiao, 1996. "Testing for independence between two covariance stationary time series," MPRA Paper 108731, University Library of Munich, Germany.

    Cited by:

    1. Fernandes, Marcelo, 2001. "Nonparametric entropy-based tests of independence between stochastic processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 413, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Ahmed, Walid M.A., 2018. "On the interdependence of natural gas and stock markets under structural breaks," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 149-161.
    3. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    4. Mariano Matilla‐García & José Miguel Rodríguez & Manuel Ruiz Marín, 2010. "A symbolic test for testing independence between time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 76-85, March.
    5. Gao, Jiti & Pan, Guangming & Yang, Yanrong, 2012. "Testing Independence for a Large Number of High–Dimensional Random Vectors," MPRA Paper 45073, University Library of Munich, Germany, revised 15 Mar 2013.
    6. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    7. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    8. Leong, Soon Heng, 2021. "Global crude oil and the Chinese oil-intensive sectors: A comprehensive causality study," Energy Economics, Elsevier, vol. 103(C).
    9. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    10. Wang, Cindy S.H. & Fan, Rui & Xie, Yiqiang, 2023. "Market systemic risk, predictability and macroeconomics news," Finance Research Letters, Elsevier, vol. 56(C).
    11. Bouhaddioui, Chafik & Roy, Roch, 2006. "On the distribution of the residual cross-correlations of infinite order vector autoregressive series and applications," Statistics & Probability Letters, Elsevier, vol. 76(1), pages 58-68, January.
    12. Chafik Bouhaddioui & Roch Roy, 2003. "On the Distribution of the Residual Cross-Correlations between Two Uncorrelated Infinite Order Vector Autoregressive Series," CIRANO Working Papers 2003s-41, CIRANO.
    13. Bertrand Caudelon & Sessi Tokpavi, 2014. "A Nonparametric Test for Granger-causality in Distribution with Application to Financial Contagion," EconomiX Working Papers 2014-18, University of Paris Nanterre, EconomiX.
    14. Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
    15. Monica Billio & Lorenzo Frattarolo & Hayette Gatfaoui & Philippe de Peretti, 2016. "Clustering in Dynamic Causal Networks as a Measure of Systemic Risk on the Euro Zone," Documents de travail du Centre d'Economie de la Sorbonne 16046, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    16. Eunhee Kim & Sangyeol Lee, 2005. "A test for independence of two stationary infinite order autoregressive processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(1), pages 105-127, March.
    17. Chu, Ba, 2023. "A distance-based test of independence between two multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    18. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    19. Mayer, Alexander, 2020. "(Consistently) testing strict exogeneity against the alternative of predeterminedness in linear time-series models," Economics Letters, Elsevier, vol. 193(C).
    20. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Post-Print hal-03528203, HAL.
    21. Ahmed, Walid M.A., 2019. "Islamic and conventional equity markets: Two sides of the same coin, or not?," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 191-205.
    22. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    23. Chafik Bouhaddioui & Roch Roy, 2004. "A Generalized Portmanteau Test for Independence of Two Infinite Order Vector Autoregressive Series," CIRANO Working Papers 2004s-06, CIRANO.
    24. Eichler, Michael, 2008. "Testing nonparametric and semiparametric hypotheses in vector stationary processes," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 968-1009, May.
    25. Hao, Jing & He, Feng, 2018. "Univariate dependence among sectors in Chinese stock market and systemic risk implication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 355-364.
    26. Xun Zhang & Fengbin Lu & Rui Tao & Shouyang Wang, 2021. "The time-varying causal relationship between the Bitcoin market and internet attention," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    27. Michael W. Robbins & Thomas J. Fisher, 2015. "Cross-Correlation Matrices for Tests of Independence and Causality Between Two Multivariate Time Series," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 459-473, October.
    28. Chafik Bouhaddioui & Roch Roy, 2006. "A Generalized Portmanteau Test For Independence Of Two Infinite‐Order Vector Autoregressive Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(4), pages 505-544, July.

Articles

  1. Sun, Jiajing & Hong, Yongmiao & Linton, Oliver & Zhao, Xiaolu, 2022. "Adjusted-range self-normalized confidence interval construction for censored dependent data," Economics Letters, Elsevier, vol. 220(C).

    Cited by:

    1. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.

  2. Quanying Lu & Yuying Sun & Yongmiao Hong & Shouyang Wang, 2022. "Forecasting interval-valued crude oil prices using asymmetric interval models," Quantitative Finance, Taylor & Francis Journals, vol. 22(11), pages 2047-2061, November.

    Cited by:

    1. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    2. Fang, Tianhui & Zheng, Chunling & Wang, Donghua, 2023. "Forecasting the crude oil prices with an EMD-ISBM-FNN model," Energy, Elsevier, vol. 263(PA).

  3. Heng, Jiani & Hong, Yongmiao & Hu, Jianming & Wang, Shouyang, 2022. "Probabilistic and deterministic wind speed forecasting based on non-parametric approaches and wind characteristics information," Applied Energy, Elsevier, vol. 306(PA).

    Cited by:

    1. Liu, Xingdou & Zhang, Li & Wang, Jiangong & Zhou, Yue & Gan, Wei, 2023. "A unified multi-step wind speed forecasting framework based on numerical weather prediction grids and wind farm monitoring data," Renewable Energy, Elsevier, vol. 211(C), pages 948-963.
    2. Wang, Yun & Xu, Houhua & Song, Mengmeng & Zhang, Fan & Li, Yifen & Zhou, Shengchao & Zhang, Lingjun, 2023. "A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting," Applied Energy, Elsevier, vol. 333(C).
    3. Lv, Sheng-Xiang & Wang, Lin, 2022. "Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization," Applied Energy, Elsevier, vol. 311(C).
    4. Wu, Han & Liang, Yan & Gao, Xiao-Zhi, 2023. "Left-right brain interaction inspired bionic deep network for forecasting significant wave height," Energy, Elsevier, vol. 278(PB).
    5. Wang, Chen & Zhang, Shenghui & Liao, Peng & Fu, Tonglin, 2022. "Wind speed forecasting based on hybrid model with model selection and wind energy conversion," Renewable Energy, Elsevier, vol. 196(C), pages 763-781.
    6. Wang, Yun & Chen, Tuo & Zou, Runmin & Song, Dongran & Zhang, Fan & Zhang, Lingjun, 2022. "Ensemble probabilistic wind power forecasting with multi-scale features," Renewable Energy, Elsevier, vol. 201(P1), pages 734-751.

  4. Yanan He & Ai Han & Yongmiao Hong & Yuying Sun & Shouyang Wang, 2021. "Forecasting crude oil price intervals and return volatility via autoregressive conditional interval models," Econometric Reviews, Taylor & Francis Journals, vol. 40(6), pages 584-606, July.

    Cited by:

    1. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    2. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Chang, Meng-Shiuh & Ju, Peijie & Liu, Yilei & Hsueh, Shao-Chieh, 2022. "Determining hedges and safe havens for stocks using interval analysis," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    4. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.

  5. Sun, Yuying & Hong, Yongmiao & Lee, Tae-Hwy & Wang, Shouyang & Zhang, Xinyu, 2021. "Time-varying model averaging," Journal of Econometrics, Elsevier, vol. 222(2), pages 974-992.
    See citations under working paper version above.
  6. Shangrong Jiang & Yuze Li & Quanying Lu & Yongmiao Hong & Dabo Guan & Yu Xiong & Shouyang Wang, 2021. "Policy assessments for the carbon emission flows and sustainability of Bitcoin blockchain operation in China," Nature Communications, Nature, vol. 12(1), pages 1-10, December.

    Cited by:

    1. Garzón Espinosa, Eduardo & Cruz Hidalgo, Esteban & Medialdea Garcia, Bibiana & Sanchez Mato, Carlos, 2023. "Money or Crypto-Gold? Problematics and Possible Worlds for Cryptocurrencies," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 76(3), pages 429-452.
    2. Jiang, Shangrong & Li, Yuze & Wang, Shouyang & Zhao, Lin, 2022. "Blockchain competition: The tradeoff between platform stability and efficiency," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1084-1097.
    3. Shunbin Zhong & Huafu Shen & Ziheng Niu & Yang Yu & Lin Pan & Yaojun Fan & Atif Jahanger, 2022. "Moving towards Environmental Sustainability: Can Digital Economy Reduce Environmental Degradation in China?," IJERPH, MDPI, vol. 19(23), pages 1-23, November.
    4. Natkamon Tovanich & Nicolas Soulié & Nicolas Heulot & Petra Isenberg, 2022. "MiningVis: visual analytics of the Bitcoin mining economy," Post-Print hal-03348145, HAL.
    5. Rina Astini & Kehkashan Ishrat & Yanto Ramli & Tafiprios Tafiprios & Kwong Wing Chong & Ooi Chee Keong, 2023. "Nexus among Crypto Trading, Environmental Degradation, Economic Growth and Energy Usage: Analysis of Top 10 Cryptofriendly Asian Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 339-347, September.
    6. Haoyang Yu & Yutong Sun & Yulin Liu & Luyao Zhang, 2023. "Bitcoin Gold, Litecoin Silver:An Introduction to Cryptocurrency's Valuation and Trading Strategy," Papers 2308.00013, arXiv.org.
    7. Calvo Pardo, Héctor & Olmo, Jose & Mancini, Tullio, 2021. "Machine Learning the Carbon Footprint of Bitcoin Mining," CEPR Discussion Papers 16267, C.E.P.R. Discussion Papers.
    8. Schinckus, Christophe, 2021. "Proof-of-work based blockchain technology and Anthropocene: An undermined situation?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    9. Sarkodie, Samuel Asumadu & Ahmed, Maruf Yakubu & Leirvik, Thomas, 2022. "Trade volume affects bitcoin energy consumption and carbon footprint," Finance Research Letters, Elsevier, vol. 48(C).
    10. Griffith, Todd & Clancey-Shang, Danjue, 2023. "Cryptocurrency regulation and market quality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    11. Zhang, Dongna & Chen, Xihui Haviour & Lau, Chi Keung Marco & Xu, Bing, 2023. "Implications of cryptocurrency energy usage on climate change," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    12. Ali, Omar & Momin, Mujtaba & Shrestha, Anup & Das, Ronnie & Alhajj, Fadia & Dwivedi, Yogesh K., 2023. "A review of the key challenges of non-fungible tokens," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    13. Wu, Xiangling & Ding, Shusheng, 2023. "The impact of the Bitcoin price on carbon neutrality: Evidence from futures markets," Finance Research Letters, Elsevier, vol. 56(C).
    14. Agur, Itai & Lavayssière, Xavier & Villegas Bauer, Germán & Deodoro, Jose & Martinez Peria, Soledad & Sandri, Damiano & Tourpe, Hervé, 2023. "Lessons from crypto assets for the design of energy efficient digital currencies," Ecological Economics, Elsevier, vol. 212(C).
    15. Rui Sun & Dayi He & Jingjing Yan & Li Tao, 2021. "Mechanism Analysis of Applying Blockchain Technology to Forestry Carbon Sink Projects Based on the Differential Game Model," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
    16. Qingjie Zhou & Panpan Zhu & Yinpeng Zhang, 2023. "Contagion Spillover from Bitcoin to Carbon Futures Pricing: Perspective from Investor Attention," Energies, MDPI, vol. 16(2), pages 1-22, January.
    17. Radosław Miśkiewicz & Krzysztof Matan & Jakub Karnowski, 2022. "The Role of Crypto Trading in the Economy, Renewable Energy Consumption and Ecological Degradation," Energies, MDPI, vol. 15(10), pages 1-15, May.
    18. Haisen Wang & Gangqiang Yang & Ziyang Yue, 2023. "Breaking through ingrained beliefs: revisiting the impact of the digital economy on carbon emissions," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    19. Chen, Hao & Xu, Chao, 2022. "The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    20. Qin, Meng & Zhang, Xiaojing & Li, Yameng & Badarcea, Roxana Maria, 2023. "Blockchain market and green finance: The enablers of carbon neutrality in China," Energy Economics, Elsevier, vol. 118(C).
    21. Lei, Nuoa & Masanet, Eric & Koomey, Jonathan, 2021. "Best practices for analyzing the direct energy use of blockchain technology systems: Review and policy recommendations," Energy Policy, Elsevier, vol. 156(C).
    22. Xiangyang Yu & Xiaojing Wang, 2023. "Research on Carbon-Trading Model of Urban Public Transport Based on Blockchain Technology," Energies, MDPI, vol. 16(6), pages 1-21, March.
    23. Baur, Dirk G. & Oll, Josua, 2022. "Bitcoin investments and climate change: A financial and carbon intensity perspective," Finance Research Letters, Elsevier, vol. 47(PA).
    24. Mingbo Zheng & Gen-Fu Feng & Xinxin Zhao & Chun-Ping Chang, 2023. "The transaction behavior of cryptocurrency and electricity consumption," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-18, December.
    25. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(C).
    26. Sood, Kirti & Singh, Simarjeet & Behl, Abhishek & Sindhwani, Rahul & Kaur, Sandeepa & Pereira, Vijay, 2023. "Identification and prioritization of the risks in the mass adoption of artificial intelligence-driven stable coins: The quest for optimal resource utilization," Resources Policy, Elsevier, vol. 81(C).
    27. Scott Fan & Elliot Gyllensvärd & Erich Farkas & Julian Schutzner, 2022. "Intervention for Cryptocurrency Emissions: A China Case Study," Working Papers hal-03737234, HAL.
    28. Elsayed, Ahmed H. & Nasir, Muhammad Ali, 2022. "Central bank digital currencies: An agenda for future research," Research in International Business and Finance, Elsevier, vol. 62(C).
    29. David Sanz-Bas & Carlos del Rosal & Sergio Luis Náñez Alonso & Miguel Ángel Echarte Fernández, 2021. "Cryptocurrencies and Fraudulent Transactions: Risks, Practices, and Legislation for Their Prevention in Europe and Spain," Laws, MDPI, vol. 10(3), pages 1-20, July.
    30. Ye, Fei & Ouyang, You & Li, Yina, 2023. "Digital investment and environmental performance: The mediating roles of production efficiency and green innovation," International Journal of Production Economics, Elsevier, vol. 259(C).
    31. Sergio Luis Náñez Alonso & Javier Jorge-Vázquez & Miguel Ángel Echarte Fernández & Ricardo Francisco Reier Forradellas, 2021. "Cryptocurrency Mining from an Economic and Environmental Perspective. Analysis of the Most and Least Sustainable Countries," Energies, MDPI, vol. 14(14), pages 1-22, July.
    32. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2022. "Dynamic volatility connectedness between thermal coal futures and major cryptocurrencies: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    33. Zhe Cheng & Tianyu Zhao & Yixin Zhu & Hanshi Li, 2022. "Evaluating the Coupling Coordinated Development between Regional Ecological Protection and High-Quality Development: A Case Study of Guizhou, China," Land, MDPI, vol. 11(10), pages 1-14, October.
    34. Xuejia Sang & Xiaopeng Leng & Linfu Xue & Xiangjin Ran, 2022. "Based on the Time-Spatial Power-Based Cryptocurrency Miner Driving Force Model, Establish a Global CO 2 Emission Prediction Framework after China Bans Cryptocurrency," Sustainability, MDPI, vol. 14(9), pages 1-18, April.
    35. Zhan, Yuanzhu & Xiong, Yu & Xing, Xinjie, 2023. "A conceptual model and case study of blockchain-enabled social media platform," Technovation, Elsevier, vol. 119(C).

  7. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.

  8. Sun, Yuying & Zhang, Xun & Hong, Yongmiao & Wang, Shouyang, 2019. "Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling," Energy Economics, Elsevier, vol. 78(C), pages 165-173.

    Cited by:

    1. Mohamed Boly & Jean-Louis Combes & Pascale Combes Motel, 2019. "How much does environment pay for politicians?," Post-Print halshs-02316151, HAL.
    2. Mohamed Boly & Jean-Louis Combes & Pascale Combes Motel, 2023. "Does environment pay for politicians?," Post-Print hal-04209496, HAL.
    3. McCulloch, Neil & Natalini, Davide & Hossain, Naomi & Justino, Patricia, 2022. "An exploration of the association between fuel subsidies and fuel riots," World Development, Elsevier, vol. 157(C).
    4. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    5. Claudiu Tiberiu Albulescu & Mihai Ioan Mutascu, 2021. "Fuel price co-movements among France, Germany and Italy: A time-frequency investigation," Post-Print hal-03529585, HAL.
    6. Zhu, Yichen & Ghoshray, Atanu, 2021. "Climate Anomalies and Its Impact on U.S. Corn and Soybean Prices," 2021 Conference, August 17-31, 2021, Virtual 315271, International Association of Agricultural Economists.
    7. Hamid Baghestani & Jorg Bley, 2020. "Do directional predictions of US gasoline prices reveal asymmetries?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 348-360, April.
    8. Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
    9. Guangyong Zhang & Lixin Tian & Wenbin Zhang & Xu Yan & Bingyue Wan & Zaili Zhen, 2020. "A Study on the Similarities and Differences of the Conventional Gasoline Spot Price Fluctuation Network between Different Harbors," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    10. Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
    11. Naixia Mou & Yanxin Xie & Tengfei Yang & Hengcai Zhang & Yoo Ri Kim, 2019. "The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road," Sustainability, MDPI, vol. 11(17), pages 1-16, September.
    12. Wood, Dallas & Larson, Justin & Jones, Jason & Galperin, Diana & Shelby, Michael & Gonzalez, Manuel, 2022. "World oil price impacts on country-specific fuel markets: Evidence of a muted global rebound effect," Energy Economics, Elsevier, vol. 111(C).
    13. Chen, Hao & Sun, Zesheng, 2021. "International crude oil price, regulation and asymmetric response of China's gasoline price," Energy Economics, Elsevier, vol. 94(C).
    14. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.

  9. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.

    Cited by:

    1. Pradeep, Siddhartha, 2022. "Impact of diesel price reforms on asymmetricity of oil price pass-through to inflation: Indian perspective," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    2. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    3. Miguel de Carvalho & Gabriel Martos, 2022. "Modeling interval trendlines: Symbolic singular spectrum analysis for interval time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 167-180, January.
    4. Wenyang Huang & Huiwen Wang & Shanshan Wang, 2021. "Dimension reduction of open-high-low-close data in candlestick chart based on pseudo-PCA," Papers 2103.16908, arXiv.org.
    5. Samadi, S. Yaser & Billard, Lynne, 2021. "Analysis of dependent data aggregated into intervals," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    6. Babel Raïssa Guemdjo Kamdem & Jules Sadefo-Kamdem & Carlos Ougouyandjou, 2020. "On Random Extended Intervals and their ARMA Processes," Working Papers hal-03169516, HAL.
    7. Zhu, Yichen & Ghoshray, Atanu, 2021. "Climate Anomalies and Its Impact on U.S. Corn and Soybean Prices," 2021 Conference, August 17-31, 2021, Virtual 315271, International Association of Agricultural Economists.
    8. Sun, Yuying & Zhang, Xun & Hong, Yongmiao & Wang, Shouyang, 2019. "Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling," Energy Economics, Elsevier, vol. 78(C), pages 165-173.
    9. Yang, Dongchuan & Guo, Ju-e & Sun, Shaolong & Han, Jing & Wang, Shouyang, 2022. "An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting," Applied Energy, Elsevier, vol. 306(PA).
    10. Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
    11. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
    12. Qing Liu & Huina Jin & Xiang Bai & Jinliang Zhang, 2023. "Prediction and Analysis of the Price of Carbon Emission Rights in Shanghai: Under the Background of COVID-19 and the Russia–Ukraine Conflict," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    13. Babel Raïssa Guemdjo Kamdem & Jules Sadefo-Kamdem & Carlos Ogouyandjou, 2021. "An Abelian Group way to study Random Extended Intervals and their ARMA Processes," Working Papers hal-03174631, HAL.
    14. Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen, 2024. "A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 366-390, March.
    15. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    16. Chang, Meng-Shiuh & Ju, Peijie & Liu, Yilei & Hsueh, Shao-Chieh, 2022. "Determining hedges and safe havens for stocks using interval analysis," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    17. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
    18. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.

  10. Wang, Xia & Hong, Yongmiao, 2018. "Characteristic Function Based Testing For Conditional Independence: A Nonparametric Regression Approach," Econometric Theory, Cambridge University Press, vol. 34(4), pages 815-849, August.

    Cited by:

    1. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    2. Ning, Jing & Pak, Daewoo & Zhu, Hong & Qin, Jing, 2022. "Conditional independence test of failure and truncation times: Essential tool for method selection," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    3. Black, Dan A. & Joo, Joonhwi & LaLonde, Robert & Smith, Jeffrey A. & Taylor, Evan J., 2022. "Simple Tests for Selection: Learning More from Instrumental Variables," Labour Economics, Elsevier, vol. 79(C).
    4. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    5. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.
    6. Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
    7. Zhou, Yeqing & Liu, Jingyuan & Zhu, Liping, 2020. "Test for conditional independence with application to conditional screening," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    8. Maomao Ding & Ruosha Li & Jin Qin & Jing Ning, 2023. "A double‐robust test for high‐dimensional gene coexpression networks conditioning on clinical information," Biometrics, The International Biometric Society, vol. 79(4), pages 3227-3238, December.

  11. Yang, Lianqiang & Hong, Yongmiao, 2017. "Adaptive penalized splines for data smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 70-83.

    Cited by:

    1. Dimitrova, Dimitrina S. & Kaishev, Vladimir K. & Lattuada, Andrea & Verrall, Richard J., 2023. "Geometrically designed variable knot splines in generalized (non-)linear models," Applied Mathematics and Computation, Elsevier, vol. 436(C).
    2. Soumya D. Mohanty & Ethan Fahnestock, 2021. "Adaptive spline fitting with particle swarm optimization," Computational Statistics, Springer, vol. 36(1), pages 155-191, March.
    3. Fabio Centofanti & Antonio Lepore & Alessandra Menafoglio & Biagio Palumbo & Simone Vantini, 2023. "Adaptive smoothing spline estimator for the function-on-function linear regression model," Computational Statistics, Springer, vol. 38(1), pages 191-216, March.

  12. Ke, Xiao & Chen, Haiqiang & Hong, Yongmiao & Hsiao, Cheng, 2017. "Do China's high-speed-rail projects promote local economy?—New evidence from a panel data approach," China Economic Review, Elsevier, vol. 44(C), pages 203-226.

    Cited by:

    1. Xu, Fei & Li, Qiangyi & Yang, Mian, 2022. "The impacts of high-speed rail on the transformation of resource-based cities in China: A market segmentation perspective," Resources Policy, Elsevier, vol. 78(C).
    2. Xiao Ke & Justin Yifu Lin & Caihui Fu & Yong Wang, 2020. "Transport Infrastructure Development and Economic Growth in China: Recent Evidence from Dynamic Panel System-GMM Analysis," Sustainability, MDPI, vol. 12(14), pages 1-22, July.
    3. Baek, Jisun & Park, WooRam, 2022. "The impact of improved passenger transport system on manufacturing plant productivity," Regional Science and Urban Economics, Elsevier, vol. 96(C).
    4. Wong, Zoey & Li, Rongrong & Peng, Dan & Kong, Qunxi, 2021. "China-european railway, investment heterogeneity, and the quality of urban economic growth," International Review of Financial Analysis, Elsevier, vol. 78(C).
    5. Dong, Lei & Du, Rui & Kahn, Matthew & Ratti, Carlo & Zheng, Siqi, 2021. "“Ghost cities” versus boom towns: Do China's high-speed rail new towns thrive?," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    6. Deng, Taotao & Wang, Dandan & Hu, Yukun & Liu, Shuang, 2020. "Did high-speed railway cause urban space expansion? ——Empirical evidence from China's prefecture-level cities," Research in Transportation Economics, Elsevier, vol. 80(C).
    7. Zhang, Shaopeng & Wang, Xiaohong, 2022. "Does innovative city construction improve the industry–university–research knowledge flow in urban China?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    8. Wang, Yongpei & Guan, Zhongyu & Zhang, Qian, 2023. "Railway opening and carbon emissions in distressed areas: Evidence from China's state-level poverty-stricken counties," Transport Policy, Elsevier, vol. 130(C), pages 55-67.
    9. Tianjiao Zhao & Xiang Xiao & Qinghui Dai, 2021. "Transportation Infrastructure Construction and High-Quality Development of Enterprises: Evidence from the Quasi-Natural Experiment of High-Speed Railway Opening in China," Sustainability, MDPI, vol. 13(23), pages 1-23, December.
    10. Liaoliao Duan & Dongxiao Niu & Weizeng Sun & Siqi Zheng, 2021. "Transportation infrastructure and capital mobility: evidence from China’s high-speed railways," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(3), pages 617-648, December.
    11. Jia, Ruining & Shao, Shuai & Yang, Lili, 2021. "High-speed rail and CO2 emissions in urban China: A spatial difference-in-differences approach," Energy Economics, Elsevier, vol. 99(C).
    12. Gao, Yanyan & Zheng, Jianghuai, 2020. "The impact of high-speed rail on innovation: An empirical test of the companion innovation hypothesis of transportation improvement with China’s manufacturing firms," World Development, Elsevier, vol. 127(C).
    13. Po Kou & Ying Han & Xiaoyuan Qi & Yuanxian Li, 2022. "Does China's policy of carbon emission trading deliver sulfur dioxide reduction co-benefits?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6224-6245, May.
    14. Kong, Dongmin & Liu, Lihua & Yang, Zhiqing, 2021. "High-speed rails and rural-urban migrants’ wages," Economic Modelling, Elsevier, vol. 94(C), pages 1030-1042.
    15. Weidong Li & Xuefang Wang & Olli-Pekka Hilmola, 2020. "Does High-Speed Railway Influence Convergence of Urban-Rural Income Gap in China?," Sustainability, MDPI, vol. 12(10), pages 1-14, May.
    16. Guo, Qingbin & Zhong, Jinrong, 2022. "The effect of urban innovation performance of smart city construction policies: Evaluate by using a multiple period difference-in-differences model," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    17. Kong, Dongmin & Liu, Lihua & Liu, Shasha, 2020. "Market information traveling on high-speed rails: The case of analyst forecasts," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    18. Jin, Mengjie & Lin, Kun-Chin & Shi, Wenming & Lee, Paul T.W. & Li, Kevin X., 2020. "Impacts of high-speed railways on economic growth and disparity in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 158-171.
    19. Chen, Fanglin & Chen, Zhongfei, 2023. "High-speed rail and happiness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    20. Li, Xiang & Cheng, Zhonghua, 2022. "Does high-speed rail improve urban carbon emission efficiency in China?," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    21. He, Xi, 2023. "Dams, cropland productivity, and economic development in China," China Economic Review, Elsevier, vol. 81(C).
    22. Dong, Yan & Huang, Jun & Wu, Ji, 2023. "Does high-speed rail affect the agglomeration of banks in China?," Emerging Markets Review, Elsevier, vol. 56(C).
    23. Wang, Yunmin & Cao, Guohua & Yan, Youliang & Wang, Jingjing, 2022. "Does high-speed rail stimulate cross-city technological innovation collaboration? Evidence from China," Transport Policy, Elsevier, vol. 116(C), pages 119-131.
    24. Wei Fan & Hongtao Xue & Cai Yi & Zhenying Xu, 2021. "TQWT-assisted statistical process control method for condition monitoring and fault diagnosis of bearings in high-speed rail," Journal of Risk and Reliability, , vol. 235(2), pages 230-240, April.
    25. Long, Fenjie & Zheng, Longfei & Song, Zhida, 2018. "High-speed rail and urban expansion: An empirical study using a time series of nighttime light satellite data in China," Journal of Transport Geography, Elsevier, vol. 72(C), pages 106-118.
    26. Jun‐Teng Ma & Tie‐Ying Liu, 2022. "Does the high‐speed rail network improve economic growth?," Papers in Regional Science, Wiley Blackwell, vol. 101(1), pages 183-208, February.
    27. Zhipeng Tang & Ziao Mei & Jialing Zou, 2021. "Does the Opening of High-Speed Railway Lines Reduce the Carbon Intensity of China’s Resource-Based Cities?," Energies, MDPI, vol. 14(15), pages 1-18, July.
    28. Lan, Xiujuan & Hu, Zheneng & Wen, Chuanhao, 2023. "Does the opening of high-speed rail enhance urban entrepreneurial activity? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    29. Yuan, Hang & Guan, Zhihua & Jiang, Changmin & Yang, Hangjun, 2023. "Peer effect in the construction of China’s high-speed rail stations: Empirical evidence from spatial econometric analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    30. Gao, Yanyan & Zheng, Jianghuai & Wang, Xin, 2022. "Does high-speed rail reduce environmental pollution? Establishment-level evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    31. Chen, Fanglin & Hao, Xinyue & Chen, Zhongfei, 2021. "Can high-speed rail improve health and alleviate health inequality? Evidence from China," Transport Policy, Elsevier, vol. 114(C), pages 266-279.
    32. Yang, Xuehui & Zhang, Huirong & Li, Yan, 2022. "High-speed railway, factor flow and enterprise innovation efficiency: An empirical analysis on micro data," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    33. Cascetta, Ennio & Cartenì, Armando & Henke, Ilaria & Pagliara, Francesca, 2020. "Economic growth, transport accessibility and regional equity impacts of high-speed railways in Italy: ten years ex post evaluation and future perspectives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 412-428.
    34. Kaan Celebi, 2020. "Quo Vadis, Britain? - Implications of the Brexit Process on the UK's Real Economy," EIIW Discussion paper disbei268, Universitätsbibliothek Wuppertal, University Library.
    35. Zhang, Xueliang & Hu, Yuqi & Lin, Yongran, 2020. "The influence of highway on local economy: Evidence from China's Yangtze River Delta region," Journal of Transport Geography, Elsevier, vol. 82(C).
    36. Yang, Xiaolan & Wang, Rui & Guo, Dongmei & Sun, Weizeng, 2020. "The reconfiguration effect of China's high-speed railway on intercity connection ——A study based on media attention index," Transport Policy, Elsevier, vol. 95(C), pages 47-56.
    37. Li, Bin & Zhao, Qizi & Shahab, Yasir & Kumar, Satish, 2023. "High-speed rail construction and labor investment efficiency: Evidence from an emerging market," Research in International Business and Finance, Elsevier, vol. 64(C).
    38. Zhaorui Guo & Kam C. Chan & Jun Huang, 2021. "The impact of executive diversity on corporate innovation: Evidence from the natural experiment of high‐speed rail in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 219-234, January.
    39. Di Matteo, Dante & Mariotti, Ilaria & Rossi, Federica, 2023. "Transport infrastructure and economic performance: An evaluation of the Milan-Bologna high-speed rail corridor," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    40. Wang, Yao & Dong, Weijia, 2022. "How China's high-speed rail promote local economy: New evidence from county-level panel data," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 67-81.
    41. Wang, Yanan & Liang, Shangkun & Kong, Dongmin & Wang, Qin, 2019. "High-speed rail, small city, and cost of debt: Firm-level evidence," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    42. Yuan, Liang & Fan, Xiaoming, 2023. "As a Chinese saying goes, ‘To get rich, first pave the way’: The opening of high-speed rail and automobile consumption in China," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    43. Li, Xiao & Qiao, Yuanbo & Shi, Lei, 2019. "Has China's war on pollution slowed the growth of its manufacturing and by how much? Evidence from the Clean Air Action," China Economic Review, Elsevier, vol. 53(C), pages 271-289.
    44. Shujie Yao & Jing Fang & Hongbo He, 2020. "Can Time–Space Compression Promote Urban Economic Growth? Evidence from China's High‐speed Rail Projects," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(5), pages 90-117, September.
    45. Li, Hui & Dong, Xiucheng & Jiang, Qingzhe & Dong, Kangyin, 2021. "Policy analysis for high-speed rail in China: Evolution, evaluation, and expectation," Transport Policy, Elsevier, vol. 106(C), pages 37-53.
    46. Li, Zekun & Chen, Zhenhua, 2023. "Predicting the future development scale of high-speed rail through the urban scaling law," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    47. Yu, Danlin & Zhang, Yaojun & Wu, Xiwei & Li, Ding & Li, Guangdong, 2021. "The varying effects of accessing high-speed rail system on China’s county development: A geographically weighted panel regression analysis," Land Use Policy, Elsevier, vol. 100(C).
    48. Yu, Danlin & Murakami, Daisuke & Zhang, Yaojun & Wu, Xiwei & Li, Ding & Wang, Xiaoxi & Li, Guangdong, 2020. "Investigating high-speed rail construction's support to county level regional development in China: An eigenvector based spatial filtering panel data analysis," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 21-37.
    49. Chen, Hongwen & Cheng, Ken & Zhang, Meiyang, 2023. "Does geographic proximity affect firms’ cross-regional development? Evidence from high-speed rail construction in China," Economic Modelling, Elsevier, vol. 126(C).
    50. Kuang, Chun & Liu, Zijie & Zhu, Wenyu, 2021. "Need for speed: High-speed rail and firm performance," Journal of Corporate Finance, Elsevier, vol. 66(C).
    51. Wang, Ke-Liang & Jiang, Wei & Miao, Zhuang, 2023. "Impact of high-speed railway on urban resilience in China: Does urban innovation matter?," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    52. Zheng, Longfei & Long, Fenjie & Chang, Zheng & Ye, Jingsong, 2019. "Ghost town or city of hope? The spatial spillover effects of high-speed railway stations in China," Transport Policy, Elsevier, vol. 81(C), pages 230-241.
    53. Wu, Shuping & Han, Dan, 2022. "Accessibility of high-speed rail (HSR) stations and HSR–air competition: Evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 262-284.
    54. Li, Shaoshuai & Li, Zhigang & Yuan, Jia, 2020. "Examining the impact of high-speed railways on land value and government revenue: Evidence from China," China Economic Review, Elsevier, vol. 63(C).
    55. Zhang, Anqi & Liu, Lihua & Liu, Guangqiang, 2020. "High-speed rail, tourist mobility, and firm value," Economic Modelling, Elsevier, vol. 90(C), pages 108-116.
    56. Wan, Liyang & Wan, Qian, 2022. "High-speed railway and the intercity transmission of epidemics: Evidence from COVID-19 in China," Economic Modelling, Elsevier, vol. 114(C).
    57. Yang, Zhiwei & Li, Can & Jiao, Jingjuan & Liu, Wei & Zhang, Fangni, 2020. "On the joint impact of high-speed rail and megalopolis policy on regional economic growth in China," Transport Policy, Elsevier, vol. 99(C), pages 20-30.
    58. Rong Wang & Li Ye & Liwen Chen, 2019. "The Impact of High-Speed Rail on Housing Prices: Evidence from China’s Prefecture-Level Cities," Sustainability, MDPI, vol. 11(13), pages 1-18, July.
    59. Shuai Liu & Guoxin Jiang & Le Chang & Lin Wang, 2022. "Can the Smart City Pilot Policy Promote High-Quality Economic Development? A Quasi-Natural Experiment Based on 239 Cities in China," Sustainability, MDPI, vol. 14(23), pages 1-17, November.
    60. Jiao, Jingjuan & Wang, Jiaoe & Zhang, Fangni & Jin, Fengjun & Liu, Wei, 2020. "Roles of accessibility, connectivity and spatial interdependence in realizing the economic impact of high-speed rail: Evidence from China," Transport Policy, Elsevier, vol. 91(C), pages 1-15.
    61. Li, Chunying & Zhang, Jinning & Lyu, Yanwei, 2022. "Does the opening of China railway express promote urban total factor productivity? New evidence based on SDID and SDDD model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    62. Jin, Mengjie & Shi, Wenming & Liu, Yu & Xu, Xiaoling & Li, Kevin X., 2022. "Heterogeneous impact of high speed railway on income distribution: A case study in China," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    63. Hu, Zhibin & Wu, Guangdong & Han, Yilong & Niu, Yanliang, 2023. "Unraveling the dynamic changes of high-speed rail network with urban development: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    64. Chen, Jean Jinghan & Cui, Chuantao & Hunt, Richard A. & Li, Leona Shao-Zhi, 2020. "External enablement of new venture creation: An exploratory, query-driven assessment of China's high-speed rail expansion," Journal of Business Venturing, Elsevier, vol. 35(6).
    65. Changsheng Xiong & Yu Tian & Xue Liu & Rong Tan & Qiaolin Luan, 2022. "The Different Impacts of Airports on the Ecological Environment under Distinct Institutional Contexts," Land, MDPI, vol. 11(2), pages 1-18, February.
    66. Dongxiao Niu & Weizeng Sun & Siqi Zheng, 2020. "Travel costs, trade, and market segmentation: Evidence from China's high‐speed railway," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1799-1825, December.
    67. Ma, Liya & Niu, Dongxiao & Sun, Weizeng, 2021. "Transportation infrastructure and entrepreneurship: Evidence from high-speed railway in China," China Economic Review, Elsevier, vol. 65(C).

  13. Yongmiao Hong & Xia Wang & Shouyang Wang, 2017. "Testing Strict Stationarity With Applications To Macroeconomic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(4), pages 1227-1277, November.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Denys Pommeret & Laurence Reboul & Anne-francoise Yao, 2023. "Testing the equality of the laws of two strictly stationary processes," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 193-214, April.
    3. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    4. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2021. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 224(2), pages 306-329.
    5. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    6. Shichao Du & Chin-Han Chan, 2023. "Baby Boom or Baby Bust After the COVID-19 Onset in the United States? Evidence from an ARIMA Time-Series Analysis," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(6), pages 1-22, December.
    7. Lee, Sangyeol & Meintanis, Simos G. & Pretorius, Charl, 2022. "Monitoring procedures for strict stationarity based on the multivariate characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    8. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.

  14. Yang, Jinqiu & Hong, Yongmiao & Ma, Shuangge, 2016. "Impact of the new health care reform on hospital expenditure in China: A case study from a pilot city," China Economic Review, Elsevier, vol. 39(C), pages 1-14.

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    1. Fu, Hongqiao & Li, Ling & Yip, Winnie, 2018. "Intended and unintended impacts of price changes for drugs and medical services: Evidence from China," Social Science & Medicine, Elsevier, vol. 211(C), pages 114-122.
    2. Longden, Thomas & Wong, Chun Yee & Haywood, Philip & Hall, Jane & van Gool, Kees, 2018. "The prevalence of persistence and related health status: An analysis of persistently high healthcare costs in the short term and medium term," Social Science & Medicine, Elsevier, vol. 211(C), pages 147-156.
    3. Jiaqi Chen & Song Xu & Jing Gao, 2020. "The Mixed Effect of China’s New Health Care Reform on Health Insurance Coverage and the Efficiency of Health Service Utilisation: A Longitudinal Approach," IJERPH, MDPI, vol. 17(5), pages 1-13, March.
    4. Zhou, Mei & Zhao, Shaoyang & Fu, Mingwei, 2021. "Supply-induced demand for medical services under price regulation: Evidence from hospital expansion in China," China Economic Review, Elsevier, vol. 68(C).
    5. Kebin Deng & Zhong Ding & Jieni Li, 2022. "Medical insurance and physician-induced demand in China: the case of hemorrhoid treatments," International Journal of Health Economics and Management, Springer, vol. 22(3), pages 257-294, September.
    6. Xueqian Song & Yongping Wei & Wei Deng & Shaoyao Zhang & Peng Zhou & Ying Liu & Jiangjun Wan, 2019. "Spatio-Temporal Distribution, Spillover Effects and Influences of China’s Two Levels of Public Healthcare Resources," IJERPH, MDPI, vol. 16(4), pages 1-18, February.
    7. Guoqiang Liu & Dakuan Qiao & Yuying Liu & Xinhong Fu, 2022. "Does Service Utilization Improve Members’ Welfare? Evidence from Citrus Cooperatives in China," Sustainability, MDPI, vol. 14(11), pages 1-20, May.
    8. See, Kok Fong & Ng, Ying Chu, 2021. "Do hospital reform and ownership matter to Shenzhen hospitals in China? A productivity analysis," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 145-155.
    9. Dong-Shang Chang & Wen-Sheng Wang & Rouwen Wang, 2018. "Identifying Critical Factors of Sustainable Healthcare Institutions’ Indicators Under Taiwan’s National Health Insurance System," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(1), pages 287-307, November.

  15. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.

    Cited by:

    1. Xiaoyong Xiao & Jing Huang, 2018. "Dynamic Connectedness of International Crude Oil Prices: The Diebold–Yilmaz Approach," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    2. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    3. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
    4. Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
    5. El Montasser, Ghassen & Malek Belhoula, Mohamed & Charfeddine, Lanouar, 2023. "Co-explosivity versus leading effects: Evidence from crude oil and agricultural commodities," Resources Policy, Elsevier, vol. 81(C).
    6. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.

  16. Chen, Bin & Hong, Yongmiao, 2016. "Detecting For Smooth Structural Changes In Garch Models," Econometric Theory, Cambridge University Press, vol. 32(3), pages 740-791, June.

    Cited by:

    1. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    2. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org, revised Aug 2023.
    3. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2021. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 224(2), pages 306-329.
    4. Feiyu Jiang & Dong Li & Ke Zhu, 2019. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Papers 1907.04147, arXiv.org, revised Oct 2020.
    5. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    6. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    7. Zongwu Cai & Xiyuan Liu, 2021. "Solving the Price Puzzle Via A Functional Coefficient Factor-Augmented VAR Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202106, University of Kansas, Department of Economics, revised Jan 2021.
    8. Maria Mohr & Natalie Neumeyer, 2021. "Nonparametric volatility change detection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 529-548, June.
    9. Lazar, Emese & Wang, Shixuan & Xue, Xiaohan, 2023. "Loss function-based change point detection in risk measures," European Journal of Operational Research, Elsevier, vol. 310(1), pages 415-431.
    10. Zongwu Cai & Xiyuan Liu, 2020. "A Functional-Coefficient VAR Model for Dynamic Quantiles with Constructing Financial Network," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202017, University of Kansas, Department of Economics, revised Oct 2020.

  17. Lu, Feng-bin & Hong, Yong-miao & Wang, Shou-yang & Lai, Kin-keung & Liu, John, 2014. "Time-varying Granger causality tests for applications in global crude oil markets," Energy Economics, Elsevier, vol. 42(C), pages 289-298.

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    1. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
    2. Rangan Gupta & Sowmya Subramaniam & Elie Bouri & Qiang Ji, 2020. "Infectious Disease-Related Uncertainty and the Safe-Haven Characteristic of US Treasury Securities," Working Papers 202078, University of Pretoria, Department of Economics.
    3. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    4. Semei Coronado & Jose N. Martinez & Victor Gualajara & Rafael Romero-Meza & Omar Rojas, 2023. "Time-Varying Granger Causality of COVID-19 News on Emerging Financial Markets: The Latin American Case," Mathematics, MDPI, vol. 11(2), pages 1-18, January.
    5. Chang, Chun-Ping & Lee, Chien-Chiang, 2015. "Do oil spot and futures prices move together?," Energy Economics, Elsevier, vol. 50(C), pages 379-390.
    6. Eduard Baumohl & Evzen Kocenda & Stefan Lyocsa & Tomas Vyrost, 2016. "Networks of volatility spillovers among stock markets," KIER Working Papers 941, Kyoto University, Institute of Economic Research.
    7. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    8. Semei Coronado & Rangan Gupta & Saban Nazlioglu & Omar Rojas, 2020. "Time-Varying Causality between Bond and Oil Markets of the United States: Evidence from Over One and Half Centuries of Data," Working Papers 202006, University of Pretoria, Department of Economics.
    9. Kais Tissaoui & Taha Zaghdoudi & Abdelaziz Hakimi & Mariem Nsaibi, 2023. "Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh Evidence Through XGBoost Modeling," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 663-687, August.
    10. Stavros Stavroyiannis, 2022. "Cointegration and ARDL specification between the Dubai crude oil and the US natural gas market," Papers 2206.03278, arXiv.org.
    11. Smyth, Russell & Narayan, Paresh Kumar, 2015. "Applied econometrics and implications for energy economics research," Energy Economics, Elsevier, vol. 50(C), pages 351-358.
    12. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    13. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    14. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    15. Caporin, Massimiliano & Costola, Michele, 2022. "Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test," Energy Economics, Elsevier, vol. 111(C).
    16. Zhuoqi Teng & Renhong Wu & Yugang He & Anibal Coronel, 2023. "Swings in Crude Oil Valuations: Analyzing Their Bearing on China’s Stock Market Returns amid the COVID-19 Pandemic Upheaval," Discrete Dynamics in Nature and Society, Hindawi, vol. 2023, pages 1-10, June.
    17. Sibande, Xolani & Demirer, Riza & Balcilar, Mehmet & Gupta, Rangan, 2023. "On the pricing effects of bitcoin mining in the fossil fuel market: The case of coal," Resources Policy, Elsevier, vol. 85(PB).
    18. Hong, Yanran & Wang, Lu & Ye, Xiaoqing & Zhang, Yaojie, 2022. "Dynamic asymmetric impact of equity market uncertainty on energy markets: A time-varying causality analysis," Renewable Energy, Elsevier, vol. 196(C), pages 535-546.
    19. Zhang, Qi & Di, Peng & Farnoosh, Arash, 2021. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models," Energy, Elsevier, vol. 223(C).
    20. Caporina, Massimiliano & Costola, Michele, 2021. "Time-varying granger causality tests for applications in global crude oil markets: A study on the DCC-MGARCH Hong test," SAFE Working Paper Series 324, Leibniz Institute for Financial Research SAFE.
    21. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
    22. Sun, Yanpeng & Mirza, Nawazish & Qadeer, Abdul & Hsueh, Hsin-Pei, 2021. "Connectedness between oil and agricultural commodity prices during tranquil and volatile period. Is crude oil a victim indeed?," Resources Policy, Elsevier, vol. 72(C).
    23. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
    24. Huang, Chuangxia & Zhao, Xian & Deng, Yunke & Yang, Xiaoguang & Yang, Xin, 2022. "Evaluating influential nodes for the Chinese energy stocks based on jump volatility spillover network," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 81-94.
    25. Deven Bathia & Riza Demirer & Rangan Gupta & Kevin Kotze, 2020. "Unemployment Fluctuations and Currency Returns in the United Kingdom: Evidence from Over One and a Half Century of Data," Working Papers 202083, University of Pretoria, Department of Economics.
    26. Mo, Bin & Chen, Cuiqiong & Nie, He & Jiang, Yonghong, 2019. "Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests," Energy, Elsevier, vol. 178(C), pages 234-251.
    27. Semei Coronado & Rangan Gupta & Besma Hkiri & Omar Rojas, 2020. "Time-Varying Spillover between Currency and Stock Markets in the United States: More than Two Centuries of Historical Evidence," Working Papers 202060, University of Pretoria, Department of Economics.
    28. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
    29. Patrick Kanda & Michael Burke & Rangan Gupta, 2017. "Time-Varying Causality between Equity and Currency Returns in the United Kingdom: Evidence from Over Two Centuries of Data," Working Papers 201778, University of Pretoria, Department of Economics.
    30. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    31. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    32. Emrah İ. Çevik & Erdal Atukeren & Turhan Korkmaz, 2018. "Oil Prices and Global Stock Markets: A Time-Varying Causality-In-Mean and Causality-in-Variance Analysis," Energies, MDPI, vol. 11(10), pages 1-22, October.
    33. Hong, Yanran & Wang, Lu & Liang, Chao & Umar, Muhammad, 2022. "Impact of financial instability on international crude oil volatility: New sight from a regime-switching framework," Resources Policy, Elsevier, vol. 77(C).
    34. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Hammoudeh, Shawkat M., 2017. "Main driving factors of the interest rate-stock market Granger causality," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 260-280.
    35. Wadud, Sania & Gronwald, Marc & Durand, Robert B. & Lee, Seungho, 2023. "Co-movement between commodity and equity markets revisited—An application of the Thick Pen method," International Review of Financial Analysis, Elsevier, vol. 87(C).
    36. Kuck, Konstantin & Schweikert, Karsten, 2017. "A Markov regime-switching model of crude oil market integration," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 16-31.
    37. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
    38. Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2019. "Time-varying causal relationship between stock market and unemployment in the United Kingdom: Historical evidence from 1855 to 2017," Journal of Multinational Financial Management, Elsevier, vol. 49(C), pages 81-88.
    39. Semei Coronado & Rangan Gupta & Besma Hkiri & Omar Rojas, 2020. "Time-Varying Spillovers between Currency and Stock Markets in the USA: Historical Evidence From More than Two Centuries," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(4), pages 44-76, December.
    40. Zhang, Yue-Jun & Bouri, Elie & Gupta, Rangan & Ma, Shu-Jiao, 2021. "Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    41. Saafi Sami & Farhat Abdeljelil & Haj Mohamed Meriem Bel, 2015. "Testing the relationships between shadow economy and unemployment: empirical evidence from linear and nonlinear tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 585-608, December.
    42. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    43. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    44. Rangan Gupta & Patrick Kanda & Aviral Kumar Tiwari & Mark E. Wohar, 2018. "Time-Varying Predictability of Oil Market Movements Over a Century of Data: The Role of US Financial Stress," Working Papers 201848, University of Pretoria, Department of Economics.
    45. Celso-Arellano, Pedro & Gualajara, Victor & Coronado, Semei & Martinez, Jose N. & Venegas-Martínez, Francisco, 2023. "Impact of the global fear index (covid-19 panic) on the S&P global indices associated with natural resources, agribusiness, energy, metals and mining: Granger Causality and Shannon and Rényi Transfer ," MPRA Paper 117138, University Library of Munich, Germany, revised 06 Feb 2023.
    46. Yuksel Haliloglu, Ebru & Sahin, Serkan & Berument, M. Hakan, 2021. "Brent–Dubai oil spread: Basic drivers," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 492-505.
    47. Xun Zhang & Fengbin Lu & Rui Tao & Shouyang Wang, 2021. "The time-varying causal relationship between the Bitcoin market and internet attention," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    48. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.
    49. Xie, Wen-Jie & Yong, Yang & Wei, Na & Yue, Peng & Zhou, Wei-Xing, 2021. "Identifying states of global financial market based on information flow network motifs," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    50. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  18. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.

    Cited by:

    1. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    2. Kheifets, Igor L., 2018. "Multivariate specification tests based on a dynamic Rosenblatt transform," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 1-14.
    3. Perera, Indeewara & Silvapulle, Mervyn J., 2023. "Bootstrap specification tests for dynamic conditional distribution models," Journal of Econometrics, Elsevier, vol. 235(2), pages 949-971.

  19. Chen, Haiqiang & Choi, Paul Moon Sub & Hong, Yongmiao, 2013. "How smooth is price discovery? Evidence from cross-listed stock trading," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 668-699.

    Cited by:

    1. Joakim Westerlund & Simon Reese & Paresh Narayan, 2017. "A Factor Analytical Approach to Price Discovery," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(3), pages 366-394, June.
    2. Dimpfl Thomas & Peter Franziska J., 2016. "Price discovery in the markets for credit risk: a Markov switching approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 233-249, June.
    3. Zouheir Ahmed Mighri & Majid Ibrahim Alsaggaf, 2019. "Asymmetric Threshold Cointegration and Nonlinear Adjustment between Oil Prices and Financial Stress," International Journal of Energy Economics and Policy, Econjournals, vol. 9(3), pages 87-105.
    4. Qadan, Mahmoud, 2018. "Switches in price discovery: Are U.S. traders more qualified in making valuations?," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 221-234.
    5. Ghadhab, Imen & Hellara, Slaheddine, 2016. "Cross-listing and value creation," Journal of Multinational Financial Management, Elsevier, vol. 37, pages 1-11.
    6. Seema Narayan & Russell Smyth, 2015. "The Financial Econometrics of Price Discovery and Predictability," Monash Economics Working Papers 06-15, Monash University, Department of Economics.
    7. Ying Jiang & Neil Kellard & Xiaoquan Liu, 2020. "Night trading and market quality: Evidence from Chinese and US precious metal futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1486-1507, October.
    8. Marta Khomyn, 2020. "Essays on Modern Market Structure," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2020.
    9. Zouheir Mighri & Faysal Mansouri, 2016. "Asymmetric price transmission within the Argentinean stock market: an asymmetric threshold cointegration approach," Empirical Economics, Springer, vol. 51(3), pages 1115-1149, November.
    10. Mehdi Arzandeh & Julieta Frank, 2019. "Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid-Ask Spread?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(5), pages 1482-1498.
    11. Arzandeh, Mehdi & Frank, Julieta, 2017. "Price Discovery in Agricultural Futures Markets: Should We Look Beyond the Best Bid-Ask Spread?," Annual Meeting, 2017, June 18-21, Montreal, Canada 259344, Canadian Agricultural Economics Society.
    12. Abdallah, Abed AL-Nasser & Abdallah, Wissam, 2019. "Does cross-listing in the US improve investment efficiency? Evidence from UK firms," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 215-231.
    13. Cepoi, Cosmin-Octavian & Anghel, Dan-Gabriel & Pop, Ionuţ Daniel, 2021. "Asymmetries and flight-to-safety effects in the price discovery process of cross-listed stocks," Economic Modelling, Elsevier, vol. 98(C), pages 302-318.
    14. Zouheir Ahmed Mighri & Majid Ibrahim Al Saggaf, 2018. "Gold - Silver Nexus: A Threshold Cointegration Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 8(5), pages 210-219.
    15. Bao, Wei & Guo, Shijun & Peng, Diefeng & Rao, Yulei, 2023. "Trading gap in holidays and price transmission: Evidence from cross-listed stocks on the A-share and H-share markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    16. Arzandeh, Mehdi & Frank, Julieta, 2017. "The Information Content of the Limit Order Book," 7th Annual Canadian Agri-Food Policy Conference, January 11-13, 2017, Ottawa, ON 253251, Canadian Agricultural Economics Society.
    17. Ghadhab, Imen & Hellara, Slaheddine, 2016. "Price discovery of cross-listed firms," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 177-188.
    18. Ghadhab, Imen & M’rad, Mouna, 2018. "Does US cross-listing come with incremental benefit for already UK cross-listed firms," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 188-204.

  20. Peng, Ling & Hong, Yongmiao, 2013. "Productivity spillovers among linked sectors," China Economic Review, Elsevier, vol. 25(C), pages 44-61.

    Cited by:

    1. Khanna, Rupika & Sharma, Chandan, 2021. "Does infrastructure stimulate total factor productivity? A dynamic heterogeneous panel analysis for Indian manufacturing industries," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 59-73.

  21. Bin Chen & Yongmiao Hong, 2012. "Testing for Smooth Structural Changes in Time Series Models via Nonparametric Regression," Econometrica, Econometric Society, vol. 80(3), pages 1157-1183, May.

    Cited by:

    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
    3. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    4. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    5. Grønborg, Niels S. & Lunde, Asger & Timmermann, Allan & Wermers, Russ, 2021. "Picking funds with confidence," Journal of Financial Economics, Elsevier, vol. 139(1), pages 1-28.
    6. Degui Li & Peter C.B. Phillips & Jiti Gao, 2017. "Kernel-Based Inference In Time-Varying Coefficient Cointegrating Regression," Cowles Foundation Discussion Papers 2109, Cowles Foundation for Research in Economics, Yale University.
    7. Gorton, Gary & Metrick, Andrew & Xie, Lei, 2021. "The flight from maturity," Journal of Financial Intermediation, Elsevier, vol. 47(C).
    8. Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Nonparametric modeling for the time-varying persistence of inflation," Economics Letters, Elsevier, vol. 225(C).
    9. Marcellino, Massimiliano & Kapetanios, George & Giraitis, Liudas, 2020. "Time-Varying Instrumental Variable Estimation," CEPR Discussion Papers 15210, C.E.P.R. Discussion Papers.
    10. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    11. Jarrow, Robert & Kwok, Simon, 2013. "Specification Tests of Calibrated Option Pricing Models," Working Papers 2013-08, University of Sydney, School of Economics, revised Dec 2014.
    12. Deshui Yu & Yayi Yan, 2023. "Joint dynamics of stock returns and cash flows: A time‐varying present‐value framework," Financial Management, Financial Management Association International, vol. 52(3), pages 513-541, September.
    13. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    14. Shahbaz, Muhammad & Shafiullah, Muhammad & Papavassiliou, Vassilios G. & Hammoudeh, Shawkat, 2017. "The CO2–growth nexus revisited: A nonparametric analysis for the G7 economies over nearly two centuries," Energy Economics, Elsevier, vol. 65(C), pages 183-193.
    15. Wu, Jilin, 2015. "Restoring monotonic power in Wald/LM-type tests," Economics Letters, Elsevier, vol. 126(C), pages 13-17.
    16. Chen, Liang & Dolado, Juan J. & Gonzalo, Jesús, 2014. "Detecting big structural breaks in large factor models," Journal of Econometrics, Elsevier, vol. 180(1), pages 30-48.
    17. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    18. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    19. Chen, Bin, 2015. "Modeling and testing smooth structural changes with endogenous regressors," Journal of Econometrics, Elsevier, vol. 185(1), pages 196-215.
    20. Shahbaz, Muhammad & Shafiullah, Muhammad & Khalid, Usman & Song, Malin, 2020. "A nonparametric analysis of energy environmental Kuznets Curve in Chinese Provinces," Energy Economics, Elsevier, vol. 89(C).
    21. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    22. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    23. Öztürk, Serda Selin & Stengos, Thanasis, 2014. "Testing for structural breaks with local smoothers: A simulation study," Economics Letters, Elsevier, vol. 125(1), pages 119-122.
    24. Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Time-varying predictability of the long horizon equity premium based on semiparametric regressions," Economics Letters, Elsevier, vol. 224(C).
    25. Timmermann, Allan & Farmer, Leland E. & Schmidt, Lawrence, 2018. "Pockets of Predictability," CEPR Discussion Papers 12885, C.E.P.R. Discussion Papers.
    26. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    27. Yu Shi & Qixuan Luo & Handong Li, 2019. "An Agent-Based Model of a Pricing Process with Power Law, Volatility Clustering, and Jumps," Complexity, Hindawi, vol. 2019, pages 1-10, February.
    28. Federico Belotti & Alessandro Casini & Leopoldo Catania & Stefano Grassi & Pierre Perron, 2023. "Simultaneous bandwidths determination for DK-HAC estimators and long-run variance estimation in nonparametric settings," Econometric Reviews, Taylor & Francis Journals, vol. 42(3), pages 281-306, February.
    29. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2023. "Optimal Local Model Averaging for Divergent-Dimensional Functional-Coefficient Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202309, University of Kansas, Department of Economics, revised Sep 2023.
    30. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    31. Haiqi Li Author-Name-First: Haiqi & Jing Zhang & Chaowen Zheng, 2023. "Estimating and Testing for Functional Coefficient Quantile Cointegrating Regression," Economics Discussion Papers em-dp2023-07, Department of Economics, University of Reading.
    32. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    33. Alessandro Casini, 2021. "Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models," Papers 2103.02981, arXiv.org.
    34. Zeng-Hua Lu, 2020. "Bahadur intercept with applications to one-sided testing," Statistical Papers, Springer, vol. 61(2), pages 645-658, April.
    35. Kashif Yousuf & Serena Ng, 2019. "Boosting High Dimensional Predictive Regressions with Time Varying Parameters," Papers 1910.03109, arXiv.org.
    36. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
    37. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    38. Casini, Alessandro, 2023. "Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstationary models," Journal of Econometrics, Elsevier, vol. 235(2), pages 372-392.
    39. Phillips, Peter C.B. & Li, Degui & Gao, Jiti, 2017. "Estimating smooth structural change in cointegration models," Journal of Econometrics, Elsevier, vol. 196(1), pages 180-195.
    40. Cleiton Guollo Taufemback, 2023. "Non‐parametric short‐ and long‐run Granger causality testing in the frequency domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 69-92, January.
    41. Smith, Simon C., 2017. "Equity premium estimates from economic fundamentals under structural breaks," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 49-61.
    42. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    43. Hao, Shiming, 2021. "True structure change, spurious treatment effect? A novel approach to disentangle treatment effects from structure changes," MPRA Paper 108679, University Library of Munich, Germany.
    44. Zongwu Cai & Ted Juhl, 2020. "The Distribution Of Rolling Regression Estimators," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202218, University of Kansas, Department of Economics, revised Dec 2022.
    45. Wan-Jiun Chen, 2022. "Toward Sustainability: Dynamics of Total Carbon Dioxide Emissions, Aggregate Income, Non-Renewable Energy, and Renewable Power," Sustainability, MDPI, vol. 14(5), pages 1-27, February.
    46. Abhimanyu Gupta & Myung Hwan Seo, 2023. "Robust Inference on Infinite and Growing Dimensional Time‐Series Regression," Econometrica, Econometric Society, vol. 91(4), pages 1333-1361, July.
    47. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    48. Kenwin Maung, 2021. "Estimating high-dimensional Markov-switching VARs," Papers 2107.12552, arXiv.org.
    49. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    50. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.
    51. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    52. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    53. Shafiullah, Muhammad & Miah, Mohammad Dulal & Alam, Md Samsul & Atif, Muhammad, 2021. "Does economic policy uncertainty affect renewable energy consumption?," Renewable Energy, Elsevier, vol. 179(C), pages 1500-1521.
    54. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    55. Alisa Yusupova & Nicos G. Pavlidis & Efthymios G. Pavlidis, 2019. "Adaptive Dynamic Model Averaging with an Application to House Price Forecasting," Papers 1912.04661, arXiv.org.
    56. Yu Bai & Massimiliano Marcellino & George Kapetanios, 2023. "Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogeneous Panels with Endogenous Regressors," Monash Econometrics and Business Statistics Working Papers 13/23, Monash University, Department of Econometrics and Business Statistics.
    57. Xue GAO & Hsu-Ling CHANG & Chi-Wei SU, 2018. "Does exchange rate always affect the number of inbound tourists significantly in China?," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(614), S), pages 55-72, Spring.
    58. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.
    59. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
    60. Alessandro Casini & Taosong Deng & Pierre Perron, 2021. "Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference," Papers 2103.01604, arXiv.org, revised Nov 2021.
    61. Yazgan, M. Ege & Özkan, Harun, 2015. "Detecting structural changes using wavelets," Finance Research Letters, Elsevier, vol. 12(C), pages 23-37.
    62. Man Wang & Kun Chen & Qin Luo & Chao Cheng, 2018. "Multi-Step Inflation Prediction with Functional Coefficient Autoregressive Model," Sustainability, MDPI, vol. 10(6), pages 1-16, May.
    63. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.
    64. Fu, Zhonghao & Hong, Yongmiao & Wang, Xia, 2023. "Testing for structural changes in large dimensional factor models via discrete Fourier transform," Journal of Econometrics, Elsevier, vol. 233(1), pages 302-331.
    65. Zhang, Rongmao & Chan, Ngai Hang & Chi, Changxiong, 2023. "Nonparametric testing for the specification of spatial trend functions," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    66. Wu, Jilin, 2016. "Detecting structural changes under nonstationary volatility," Economics Letters, Elsevier, vol. 146(C), pages 151-154.
    67. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    68. Christis Katsouris, 2022. "Partial Sum Processes of Residual-Based and Wald-type Break-Point Statistics in Time Series Regression Models," Papers 2202.00141, arXiv.org, revised Feb 2022.
    69. Chiou, Yan-Yu & Chen, Mei-Yuan & Chen, Jau-er, 2018. "Nonparametric regression with multiple thresholds: Estimation and inference," Journal of Econometrics, Elsevier, vol. 206(2), pages 472-514.
    70. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
    71. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).
    72. Jiti Gao & Oliver Linton & Bin Peng, 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Monash Econometrics and Business Statistics Working Papers 9/22, Monash University, Department of Econometrics and Business Statistics.
    73. Yan-Yu Chiou & Mei-Yuan Chen & Jau-er Chen, 2017. "Nonparametric Regression with Multiple Thresholds: Estimation and Inference," Papers 1705.09418, arXiv.org, revised Feb 2018.
    74. Porter, Jack & Yu, Ping, 2015. "Regression discontinuity designs with unknown discontinuity points: Testing and estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 132-147.

  22. Hong, Yongmiao & Lin, Hai & Wu, Chunchi, 2012. "Are corporate bond market returns predictable?," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2216-2232.

    Cited by:

    1. Montgomery, William & Raza, Ahmad & Ülkü, Numan, 2019. "Tests of technical trading rules and the 52-week high strategy in the corporate bond market," Global Finance Journal, Elsevier, vol. 40(C), pages 85-103.
    2. Demir Bektić, 2018. "The low beta anomaly: A corporate bond investor's perspective," Review of Financial Economics, John Wiley & Sons, vol. 36(4), pages 300-306, October.
    3. Zhang, Tai-Wei & Wu, Wei-Hwa, 2014. "The asymmetric predictability of high-yield bonds," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 146-155.
    4. Tsai, Hui-Ju, 2014. "The informational efficiency of bonds and stocks: The role of institutional sized bond trades," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 34-45.
    5. Zheyao Pan, 2018. "A state‐price volatility index for the U.S. government bond market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 573-597, November.
    6. Jon Danielsson & Marcela Valenzuela & Ilknur Zer, 2023. "The Impact of Risk Cycles on Business Cycles: A Historical View," The Review of Financial Studies, Society for Financial Studies, vol. 36(7), pages 2922-2961.
    7. Elroi Hadad & Haim Kedar-Levy, 2022. "The Impact of Retail Investors Sentiment on Conditional Volatility of Stocks and Bonds," Papers 2208.01538, arXiv.org.
    8. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    9. Gu, Rongbao & Shao, Yanmin, 2016. "How long the singular value decomposed entropy predicts the stock market? — Evidence from the Dow Jones Industrial Average Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 150-161.
    10. Adams, Carol A. & Potter, Brad & Singh, Prakash J. & York, Jodi, 2016. "Exploring the implications of integrated reporting for social investment (disclosures)," The British Accounting Review, Elsevier, vol. 48(3), pages 283-296.
    11. Tolikas, Konstantinos, 2016. "The relative informational efficiency of corporate retail bonds: Evidence from the London Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 191-201.
    12. Demir Bektić & Tobias Regele, 2018. "Exploiting uncertainty with market timing in corporate bond markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 79-92, March.
    13. Shynkevich, Andrei, 2016. "Predictability in bond returns using technical trading rules," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 55-69.
    14. Lin, Hai & Wang, Junbo & Wu, Chunchi, 2014. "Predictions of corporate bond excess returns," Journal of Financial Markets, Elsevier, vol. 21(C), pages 123-152.
    15. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
    16. Tolikas, Konstantinos & Topaloglou, Nikolas, 2017. "Is default risk priced equally fast in the credit default swap and the stock markets? AN empirical investigation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 39-57.
    17. Gu, Rongbao, 2017. "Multiscale Shannon entropy and its application in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 215-224.
    18. Gormus, Alper & Nazlioglu, Saban & Soytas, Ugur, 2018. "High-yield bond and energy markets," Energy Economics, Elsevier, vol. 69(C), pages 101-110.
    19. Li, Jiacui, 2022. "Endogenous inattention and risk-specific price underreaction in corporate bonds," Journal of Financial Economics, Elsevier, vol. 145(2), pages 595-615.
    20. Cao, N. & Galvani, V. & Gubellini, S., 2017. "Firm-specific stock and bond predictability: New evidence from Canada," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 174-192.
    21. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    22. Pham, Son D. & Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2021. "The liquidity of active ETFs," Global Finance Journal, Elsevier, vol. 49(C).
    23. Ganchev, Alexander, 2023. "The Behaviour of Chinese Government Bond Yield Curve before and during the COVID-19 Pandemic," MPRA Paper 117626, University Library of Munich, Germany.

  23. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.

    Cited by:

    1. Esha Saha & Pradip Kumar Ray, 2019. "Modelling and analysis of healthcare inventory management systems," OPSEARCH, Springer;Operational Research Society of India, vol. 56(4), pages 1179-1198, December.
    2. Rosati, Nicoletta & Bellia, Mario & Matos, Pedro Verga & Oliviera, Vasco, 2019. "Ratings matter: announcements in times of crisis and the dynamics of stock markets," Working Papers 2019-08, Joint Research Centre, European Commission.
    3. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    4. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    5. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    6. Dillschneider, Yannick & Maurer, Raimond, 2019. "Functional Ross recovery: Theoretical results and empirical tests," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).

  24. Yongmiao Hong & Yoon‐Jin Lee, 2011. "Detecting misspecifications in autoregressive conditional duration models and non‐negative time‐series processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(1), pages 1-32, January.

    Cited by:

    1. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    2. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    3. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
    4. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    5. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.

  25. Li, Hongquan & Hong, Yongmiao, 2011. "Financial volatility forecasting with range-based autoregressive volatility model," Finance Research Letters, Elsevier, vol. 8(2), pages 69-76, June.

    Cited by:

    1. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    2. Kumar, Dilip & Maheswaran, S., 2014. "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 128-140.
    3. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
    4. Díaz-Mendoza, Ana-Carmen & Pardo, Angel, 2020. "Holidays, weekends and range-based volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    5. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Tan, Shay-Kee & Chan, Jennifer So-Kuen & Ng, Kok-Haur, 2020. "On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure," Finance Research Letters, Elsevier, vol. 32(C).
    7. Alia Afzal & Philipp Sibbertsen, 2023. "Long Memory, Spurious Memory: Persistence in Range-Based Volatility of Exchange Rates," Open Economies Review, Springer, vol. 34(4), pages 789-811, September.
    8. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.
    9. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
    10. Dong, Xi & Feng, Shu & Ling, Leng & Song, Pingping, 2017. "Dynamic autocorrelation of intraday stock returns," Finance Research Letters, Elsevier, vol. 20(C), pages 274-280.
    11. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    12. Fiszeder, Piotr & Perczak, Grzegorz, 2016. "Low and high prices can improve volatility forecasts during periods of turmoil," International Journal of Forecasting, Elsevier, vol. 32(2), pages 398-410.
    13. Dilip Kumar, 2016. "Sudden changes in crude oil price volatility: an application of extreme value volatility estimator," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(3/4), pages 215-234.
    14. Koutmos, Dimitrios & Song, Wei, 2014. "Speculative dynamics and price behavior in the Shanghai Stock Exchange," Research in International Business and Finance, Elsevier, vol. 31(C), pages 74-86.
    15. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    16. Ying Jiang & Shamim Ahmed & Xiaoquan Liu, 2017. "Volatility forecasting in the Chinese commodity futures market with intraday data," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 1123-1173, May.
    17. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.
    18. Dilip Kumar, 2016. "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences 3205528, International Institute of Social and Economic Sciences.
    19. Lai, Yu-Sheng, 2022. "Improving hedging performance by using high–low range," Finance Research Letters, Elsevier, vol. 48(C).
    20. Piotr Fiszeder & Grzegorz Perczak, 2013. "A new look at variance estimation based on low, high and closing prices taking into account the drift," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 456-481, November.
    21. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    22. Tomasz Skoczylas, 2013. "Modelowanie i prognozowanie zmienności przy użyciu modeli opartych o zakres wahań," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 35.
    23. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    24. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    25. Bayraci, Selcuk & Demiralay, Sercan, 2013. "Conditional Autoregregressive Range (CARR) Based Volatility Spillover Index For the Eurozone Markets," MPRA Paper 51909, University Library of Munich, Germany.
    26. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    27. Xie, Haibin & Qi, Nan & Wang, Shouyang, 2019. "A new variant of RealGARCH for volatility modeling," Finance Research Letters, Elsevier, vol. 28(C), pages 438-443.
    28. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
    29. Arnerić, Josip & Matković, Mario & Sorić, Petar, 2019. "Comparison of range-based volatility estimators against integrated volatility in European emerging markets," Finance Research Letters, Elsevier, vol. 28(C), pages 118-124.
    30. Ahmed, Walid M.A., 2017. "The impact of foreign equity flows on market volatility during politically tranquil and turbulent times: The Egyptian experience," Research in International Business and Finance, Elsevier, vol. 40(C), pages 61-77.
    31. Wu, Xinyu & Hou, Xinmeng, 2020. "Forecasting volatility with component conditional autoregressive range model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    32. Vipul Kumar Singh, 2013. "Effectiveness of volatility models in option pricing: evidence from recent financial upheavals," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 10(3), pages 352-375, October.
    33. Hassan, M. Kabir & Kayhana, Selim & Bayatb, Tayfur, 2016. "The Relation between Return and Volatility in ETFs Traded in Borsa Istanbul: Is there any Difference between Islamic and Conventional ETFs?," Islamic Economic Studies, The Islamic Research and Training Institute (IRTI), vol. 24, pages 45-76.

  26. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.

    Cited by:

    1. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    2. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    3. Maghyereh, Aktham I. & Awartani, Basel & Abdoh, Hussein, 2019. "The co-movement between oil and clean energy stocks: A wavelet-based analysis of horizon associations," Energy, Elsevier, vol. 169(C), pages 895-913.
    4. Takashi Isogai, 2017. "Analysis of Dynamic Correlation of Japanese Stock Returns with Network Clustering," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 193-220, September.

  27. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.

    Cited by:

    1. Bin Chen & Jinho Choi & Juan Carlos Escanciano, 2015. "Testing for Fundamental Vector Moving Average Representations," CAEPR Working Papers 2015-022, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Lazar, Emese & Qi, Shuyuan, 2022. "Model risk in the over-the-counter market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 769-784.
    3. Emese Lazar & Shuyuan Qi & Radu Tunaru, 2020. "Measures of Model Risk in Continuous-time Finance Models," Papers 2010.08113, arXiv.org, revised Oct 2020.

  28. Hong, Yongmiao & Lin, Hai & Wang, Shouyang, 2010. "Modeling the dynamics of Chinese spot interest rates," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1047-1061, May.

    Cited by:

    1. Rongrong Sun, 2018. "Monetary Policy Announcements and Market Interest Rates Response: Evidence from China," CFDS Discussion Paper Series 2018/5, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    2. Ka-Fai Li & Cho-Hoi Hui & Tsz-Kin Chung, 2012. "Determinants and Dynamics of Price Disparity in Onshore and Offshore Renminbi Forward Exchange Rate Markets," Working Papers 242012, Hong Kong Institute for Monetary Research.
    3. Xie, Qiwei & Cheng, Lu & Liu, Ranran & Zheng, Xiaolong & Li, Jingyu, 2023. "COVID-19 and risk spillovers of China's major financial markets: Evidence from time-varying variance decomposition and wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 52(C).
    4. Löchel, H. & Packham, N. & Walisch, F., 2016. "Determinants of the onshore and offshore Chinese government yield curves," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 77-93.
    5. Loechel, Horst & Packham, Natalie & Walisch, Fabian, 2013. "Determinants of the onshore and offshore Chinese Government yield curves," Frankfurt School - Working Paper Series 202, Frankfurt School of Finance and Management.
    6. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
    7. Nowman, Khalid Ben, 2010. "Modelling the UK and Euro yield curves using the Generalized Vasicek model: Empirical results from panel data for one and two factor models," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 334-341, December.
    8. Xuejun Jin & Frank M. Song & Yizhong Wang & Yi Zhong, 2014. "Interest Rate Pass-through in a Dual-track System: Evidence from China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 22(4), pages 21-39, July.

  29. Chen, Bin & Hong, Yongmiao, 2010. "Characteristic Function–Based Testing For Multifactor Continuous-Time Markov Models Via Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1115-1179, August.

    Cited by:

    1. Breunig, Christoph & Hoderlein, Stefan, 2018. "Specification Testing in Random Coefficient Models," Rationality and Competition Discussion Paper Series 77, CRC TRR 190 Rationality and Competition.
    2. Chen, Songxi & Peng, Liang & Yu, Cindy, 2013. "Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions," MPRA Paper 46273, University Library of Munich, Germany.
    3. Dante Amengual & Marine Carrasco & Enrique Sentana, 2017. "Testing Distributional Assumptions Using a Continuum of Moments," Working Papers wp2017_1709, CEMFI.
    4. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
    5. Nadarajah, Saralees & Chan, Stephen & Afuecheta, Emmanuel, 2013. "On the characteristic function for asymmetric Student t distributions," Economics Letters, Elsevier, vol. 121(2), pages 271-274.
    6. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
    7. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    8. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    9. Fuchun Li, 2015. "Testing for the Diffusion Matrix in a Continuous-Time Markov Process Model with Applications to the Term Structure of Interest Rates," Staff Working Papers 15-17, Bank of Canada.
    10. Song, Zhaogang, 2011. "A martingale approach for testing diffusion models based on infinitesimal operator," Journal of Econometrics, Elsevier, vol. 162(2), pages 189-212, June.

  30. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.

    Cited by:

    1. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
    2. Tam Hoang-Nhat Dang & Nhan Thien Nguyen & Duc Hong Vo, 2023. "Sectoral volatility spillovers and their determinants in Vietnam," Economic Change and Restructuring, Springer, vol. 56(1), pages 681-700, February.
    3. Atukeren, Erdal & Cevik, Emrah Ismail & Korkmaz, Turhan, 2015. "Downside Business Confidence Spillovers in Europe: Evidence from Causality-in-Risk Tests," MPRA Paper 76038, University Library of Munich, Germany.
    4. Zheng Yang & Anthony H. Tu & Yong Zeng, 2014. "Dynamic linkages between Asian stock prices and exchange rates: new evidence from causality in quantiles," Applied Economics, Taylor & Francis Journals, vol. 46(11), pages 1184-1201, April.
    5. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    6. Vassilios Babalos & Mehmet Balcilar & Tumisang B. Loate & Shingie Chisoro, 2018. "Did Baltic stock markets offer diversification benefits during the recent financial turmoil? Novel evidence from a nonparametric causality-in-quantiles test," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 29-47, February.
    7. Marcin Faldzinski & Magdalena Osinska, 2016. "Volatility estimators in econometric analysis of risk transfer on capital markets," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 21-35.
    8. Fabian Hollstein & Marcel Prokopczuk & Christoph Würsig, 2020. "Volatility term structures in commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 527-555, April.
    9. Lucia Bellenzier & Jørgen Vitting Andersen & Giulia Rotundo, 2015. "Contagion in the world's stock exchanges seen as a set of coupled oscillators," Documents de travail du Centre d'Economie de la Sorbonne 15078, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    10. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    11. Cui, Jinxin & Goh, Mark & Li, Binlin & Zou, Huiwen, 2021. "Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives," Energy, Elsevier, vol. 216(C).
    12. Jian, Zhihong & Zhu, Zhican & Zhou, Jie & Wu, Shuai, 2020. "Intraday price jumps, market liquidity, and the magnet effect of circuit breakers," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 168-186.
    13. Deng, Chao & Su, Xiaojian & Wang, Gangjin & Peng, Cheng, 2022. "The existence of flight-to-quality under extreme conditions: Evidence from a nonlinear perspective in Chinese stocks and bonds' sectors," Economic Modelling, Elsevier, vol. 113(C).
    14. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    15. Bellenzier, Lucia & Vitting Andersen, Jørgen & Rotundo, Giulia, 2016. "Contagion in the world's stock exchanges seen as a set of coupled oscillators," Economic Modelling, Elsevier, vol. 59(C), pages 224-236.
    16. Dilip Kumar, 2017. "A Study of Risk Spillover in the Crude Oil and the Natural Gas Markets," Global Business Review, International Management Institute, vol. 18(6), pages 1465-1477, December.
    17. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    18. Jian, Zhihong & Wu, Shuai & Zhu, Zhican, 2018. "Asymmetric extreme risk spillovers between the Chinese stock market and index futures market: An MV-CAViaR based intraday CoVaR approach," Emerging Markets Review, Elsevier, vol. 37(C), pages 98-113.
    19. Li, Jianping & Li, Jingyu & Zhu, Xiaoqian & Yao, Yinhong & Casu, Barbara, 2020. "Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S," International Review of Financial Analysis, Elsevier, vol. 71(C).
    20. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    21. Mazzarisi, Piero & Zaoli, Silvia & Lillo, Fabrizio & Delgado, Luis & Gurtner, Gérald, 2020. "New centrality and causality metrics assessing air traffic network interactions," Journal of Air Transport Management, Elsevier, vol. 85(C).
    22. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    23. Zhang-Hangjian Chen & Xiang Gao & Apicha Insuwan, 2023. "Dynamic information spillover between Chinese carbon and stock markets under extreme weather shocks," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    24. Li, Jingyu & Yao, Yanzhen & Li, Jianping & Zhu, Xiaoqian, 2019. "Network-based estimation of systematic and idiosyncratic contagion: The case of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
    25. Shen, Yifan, 2018. "International risk transmission of stock market movements," Economic Modelling, Elsevier, vol. 69(C), pages 220-236.
    26. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2022. "Temporal networks in the analysis of financial contagion," Working Paper Series 2667, European Central Bank.
    27. Carlo Campajola & Fabrizio Lillo & Daniele Tantari, 2019. "Unveiling the relation between herding and liquidity with trader lead-lag networks," Papers 1909.10807, arXiv.org, revised Mar 2020.
    28. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    29. Jian, Zhihong & Li, Xupei, 2021. "Skewness-based market integration: A systemic risk measure across international equity markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    30. Joëts, Marc, 2014. "Energy price transmissions during extreme movements," Economic Modelling, Elsevier, vol. 40(C), pages 392-399.
    31. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.
    32. Neto, David, 2022. "Revisiting spillovers between investor attention and cryptocurrency markets using noisy independent component analysis and transfer entropy," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    33. Sara Boni & Massimiliano Caporin & Francesco Ravazzolo, 2024. "Nowcasting Inflation at Quantiles: Causality from Commodities," BEMPS - Bozen Economics & Management Paper Series BEMPS102, Faculty of Economics and Management at the Free University of Bozen.
    34. Matteo Farnè & Angela Montanari, 2022. "A Bootstrap Method to Test Granger-Causality in the Frequency Domain," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 935-966, March.
    35. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    36. Khamis Hamed Al‐Yahyaee & Syed Jawad Hussain Shahzad & Walid Mensi & Seong‐Min Yoon, 2021. "Is there a systemic risk between Sharia, Sukuk, and GCC stock markets? A ΔCoVaR risk metric‐based copula approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2904-2926, April.
    37. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    38. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    39. Yao, Xiaoyang & Le, Wei & Sun, Xiaolei & Li, Jianping, 2020. "Financial stress dynamics in China: An interconnectedness perspective," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 217-238.
    40. Emrah Ismail Cevik & Sel Dibooglu & Atif Awad Abdallah & Eisa Abdulrahman Al-Eisa, 2021. "Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia," International Economics and Economic Policy, Springer, vol. 18(1), pages 157-175, February.
    41. Li, Dongxin & Hong, Yanran & Wang, Lu & Xu, Pengfei & Pan, Zhigang, 2022. "Extreme risk transmission among bitcoin and crude oil markets," Resources Policy, Elsevier, vol. 77(C).
    42. Xiao, Di & Wang, Jun, 2020. "Dynamic complexity and causality of crude oil and major stock markets," Energy, Elsevier, vol. 193(C).
    43. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    44. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    45. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    46. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    47. Shen, Yifan & Shi, Xunpeng & Variam, Hari Malamakkavu Padinjare, 2018. "Risk transmission mechanism between energy markets: A VAR for VaR approach," Energy Economics, Elsevier, vol. 75(C), pages 377-388.
    48. Dinghai Xu & Jingru Ji & Donghua Wang, 2018. "Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market," Working Papers 1806, University of Waterloo, Department of Economics, revised 09 Jan 2018.
    49. Caporin, Massimiliano & Costola, Michele, 2022. "Time-varying Granger causality tests in the energy markets: A study on the DCC-MGARCH Hong test," Energy Economics, Elsevier, vol. 111(C).
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    1. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
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    1. Atukeren, Erdal & Cevik, Emrah Ismail & Korkmaz, Turhan, 2015. "Downside Business Confidence Spillovers in Europe: Evidence from Causality-in-Risk Tests," MPRA Paper 76038, University Library of Munich, Germany.
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    3. Donghua Wang & Yang Xin & Xiaohui Chang & Xingze Su, 2021. "Realized volatility forecasting and volatility spillovers: Evidence from Chinese non‐ferrous metals futures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2713-2731, April.
    4. Go, You-How & Lau, Wee-Yeap, 2021. "Extreme risk spillovers between crude palm oil prices and exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Qunwei Wang & Xingyu Dai & Dequn Zhou, 2020. "Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1117-1150, April.
    6. Wang, Xinya & Lucey, Brian & Huang, Shupei, 2022. "Can gold hedge against oil price movements: Evidence from GARCH-EVT wavelet modeling," Journal of Commodity Markets, Elsevier, vol. 27(C).
    7. Todorova, Neda & Worthington, Andrew & Souček, Michael, 2014. "Realized volatility spillovers in the non-ferrous metal futures market," Resources Policy, Elsevier, vol. 39(C), pages 21-31.
    8. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Stanley, H. Eugene, 2016. "Extreme risk spillover effects in world gold markets and the global financial crisis," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 55-77.
    9. Okur, Mustafa & Cevik, Emrah Ismail, 2013. "Testing intraday volatility spillovers in Turkish capital markets: evidence from ISE," MPRA Paper 71477, University Library of Munich, Germany, revised 2013.
    10. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2013. "Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1795-1802.
    11. Gkillas, Konstantinos & Konstantatos, Christoforos & Floros, Christos & Tsagkanos, Athanasios, 2021. "Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis," International Review of Financial Analysis, Elsevier, vol. 74(C).
    12. Yu, Hui & Ding, Yinghui & Sun, Qingru & Gao, Xiangyun & Jia, Xiaoliang & Wang, Xinya & Guo, Sui, 2021. "Multi-scale comovement of the dynamic correlations between copper futures and spot prices," Resources Policy, Elsevier, vol. 70(C).
    13. Arık, Evren & Mutlu, Elif, 2014. "Chinese steel market in the post-futures period," Resources Policy, Elsevier, vol. 42(C), pages 10-17.
    14. Guo, Jin, 2018. "Co-movement of international copper prices, China's economic activity, and stock returns: Structural breaks and volatility dynamics," Global Finance Journal, Elsevier, vol. 36(C), pages 62-77.
    15. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2011. "Structural changes and volatility transmission in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4317-4324.
    16. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.

  33. Hong, Yongmiao & Lee, Yoon-Jin, 2007. "An Improved Generalized Spectral Test For Conditional Mean Models In Time Series With Conditional Heteroskedasticity Of Unknown Form," Econometric Theory, Cambridge University Press, vol. 23(1), pages 106-154, February.

    Cited by:

    1. Hamidi Sahneh, Mehdi, 2015. "Are the shocks obtained from SVAR fundamental?," MPRA Paper 65126, University Library of Munich, Germany.
    2. Jarrow, Robert & Kwok, Simon, 2013. "Specification Tests of Calibrated Option Pricing Models," Working Papers 2013-08, University of Sydney, School of Economics, revised Dec 2014.
    3. Péter Farkas, 2013. "Counting Process Generated by Boundary-crossing Events. Theory and Statistical Applications," CEU Working Papers 2013_4, Department of Economics, Central European University.
    4. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    5. Karim M. Abadir & Gabriel Talmain, 2012. "Beyond Co-Integration: Modelling Co-Movements in Macro finance," Working Paper series 25_12, Rimini Centre for Economic Analysis.

  34. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.

    Cited by:

    1. Roch, Oriol, 2013. "Histogram-based prediction of directional price relatives," Finance Research Letters, Elsevier, vol. 10(3), pages 110-115.
    2. Baghestani, Hamid & Toledo, Hugo, 2017. "Do analysts' forecasts of term spread differential help predict directional change in exchange rates?," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 62-69.
    3. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    4. Haibin Xie & Yuying Sun & Pengying Fan, 2023. "Return direction forecasting: a conditional autoregressive shape model with beta density," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    5. Pippenger, John, 2012. "The Fragility of Overshooting," University of California at Santa Barbara, Economics Working Paper Series qt4rd5j98c, Department of Economics, UC Santa Barbara.
    6. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    7. Stanislav Anatolyev & Jozef Barunik, 2017. "Forecasting dynamic return distributions based on ordered binary choice," Papers 1711.05681, arXiv.org, revised Jan 2019.
    8. Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
    9. Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    10. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    11. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.
    12. Pippenger, John, 2008. "Freely Floating Exchange Rates Do Not Systematically Overshoot," University of California at Santa Barbara, Economics Working Paper Series qt97m8z6hw, Department of Economics, UC Santa Barbara.
    13. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
    14. Y. Kahiri & A. Shmilovici & S. Hauser, 2006. "Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm," Computing in Economics and Finance 2006 256, Society for Computational Economics.
    15. Anatolyev Stanislav, 2009. "Multi-Market Direction-of-Change Modeling Using Dependence Ratios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    16. Yi Xiao & Keying Li & Yi Hu & Jin Xiao & Shouyang Wang, 2020. "Combining STRIPAT model and gated recurrent unit for forecasting nature gas consumption of China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1325-1343, October.
    17. Pippenger, John, 2009. "Dornbusch Was Wrong: There is no Convincing Evidence of Overshooting, Delayed or Otherwise," University of California at Santa Barbara, Economics Working Paper Series qt78k0b5zw, Department of Economics, UC Santa Barbara.
    18. Becker, Janis & Leschinski, Christian, 2018. "Directional Predictability of Daily Stock Returns," Hannover Economic Papers (HEP) dp-624, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    19. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, New Economic School (NES).
    20. Shmilovici Armin & Ben-Gal Irad, 2012. "Predicting Stock Returns Using a Variable Order Markov Tree Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-33, December.
    21. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    22. Bruno Spilak & Wolfgang Karl Härdle, 2022. "Tail-Risk Protection: Machine Learning Meets Modern Econometrics," Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211, Springer.
    23. Rangan Gupta & Vasilios Plakandaras, 2018. "Efficiency in BRICS Currency Markets using Long-Spans of Data: Evidence from Model-Free Tests of Directional Predictability," Working Papers 201836, University of Pretoria, Department of Economics.
    24. Riza Demirer & Rangan Gupta & Hossein Hassani & Xu Huang, 2020. "Time-Varying Risk Aversion and the Profitability of Carry Trades: Evidence from the Cross-Quantilogram," Economies, MDPI, vol. 8(1), pages 1-12, March.
    25. Ulm, M. & Hambuckers, J., 2022. "Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 125-148.

  35. Hong, Yongmiao & Li, Haitao & Zhao, Feng, 2007. "Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates," Journal of Econometrics, Elsevier, vol. 141(2), pages 736-776, December.

    Cited by:

    1. Atukeren, Erdal & Cevik, Emrah Ismail & Korkmaz, Turhan, 2015. "Downside Business Confidence Spillovers in Europe: Evidence from Causality-in-Risk Tests," MPRA Paper 76038, University Library of Munich, Germany.
    2. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    4. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    5. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    6. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    7. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    8. Emrah Ismail Cevik & Sel Dibooglu & Atif Awad Abdallah & Eisa Abdulrahman Al-Eisa, 2021. "Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia," International Economics and Economic Policy, Springer, vol. 18(1), pages 157-175, February.
    9. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    10. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    11. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
    12. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    13. Hong, Yongmiao & Lin, Hai & Wang, Shouyang, 2010. "Modeling the dynamics of Chinese spot interest rates," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1047-1061, May.
    14. Charlie X. Cai & Qi Zhang, 2016. "High†Frequency Exchange Rate Forecasting," European Financial Management, European Financial Management Association, vol. 22(1), pages 120-141, January.
    15. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    16. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
    17. Jian Wang & Jason J. Wu, 2008. "The Taylor rule and forecast intervals for exchange rates," Globalization Institute Working Papers 22, Federal Reserve Bank of Dallas.
    18. Ko, Stanley I.M. & Park, Sung Y., 2013. "Multivariate density forecast evaluation: A modified approach," International Journal of Forecasting, Elsevier, vol. 29(3), pages 431-441.
    19. Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
    20. Meade, N. & Beasley, J.E. & Adcock, C.J., 2021. "Quantitative portfolio selection: Using density forecasting to find consistent portfolios," European Journal of Operational Research, Elsevier, vol. 288(3), pages 1053-1067.
    21. Yun, Jaeho, 2014. "Out-of-sample density forecasts with affine jump diffusion models," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 74-87.
    22. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
    23. Dietmar Janetzko, 2014. "Predictive modeling in turbulent times – What Twitter reveals about the EUR/USD exchange rate," Netnomics, Springer, vol. 15(2), pages 69-106, September.
    24. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
    25. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    26. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
    27. Lorenzo Reus & Guillermo Alexander Sepúlveda-Hurtado, 2023. "Foreign exchange trading and management with the stochastic dual dynamic programming method," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
    28. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    29. Svetlana Mira & Nicholas Taylor, 2013. "An International Perspective on Risk Management Quality," European Financial Management, European Financial Management Association, vol. 19(5), pages 935-955, November.
    30. Diep Duong & Norman Swanson, 2013. "Density and Conditional Distribution Based Specification Analysis," Departmental Working Papers 201312, Rutgers University, Department of Economics.
    31. Alexey Balaev, 2011. "Modeling multivariate parametric densities of financial returns (in Russian)," Quantile, Quantile, issue 9, pages 39-60, July.
    32. Dietmar Janetzko, 2014. "Using Twitter to Model the EUR/USD Exchange Rate," Papers 1402.1624, arXiv.org.
    33. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.

  36. Egorov, Alexei V. & Hong, Yongmiao & Li, Haitao, 2006. "Validating forecasts of the joint probability density of bond yields: Can affine models beat random walk?," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 255-284.

    Cited by:

    1. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    2. Abdymomunov, Azamat & Kang, Kyu Ho & Kim, Ki Jeong, 2016. "Can credit spreads help predict a yield curve?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 39-61.
    3. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    4. Hitesh Doshi & Kris Jacobs & Rui Liu, 2021. "Information in the Term Structure: A Forecasting Perspective," Management Science, INFORMS, vol. 67(8), pages 5255-5277, August.
    5. Almeida, Caio & Vicente, José, 2009. "Are interest rate options important for the assessment of interest rate risk?," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1376-1387, August.
    6. René Garcia & Richard Luger, 2005. "The Canadian Macroeconomy and the Yield Curve: An Equilibrium-Based Approach," Staff Working Papers 05-36, Bank of Canada.
    7. Philippe Lambert & Sébastien Laurent & David Veredas, 2012. "Testing conditional asymmetry. A residual based approach," ULB Institutional Repository 2013/136195, ULB -- Universite Libre de Bruxelles.
    8. René Garcia & Richard Luger, 2009. "Risk Aversion, Intertemporal Substitution, and the Term Structure of Interest Rates," CIRANO Working Papers 2009s-20, CIRANO.
    9. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    10. Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    11. Peter Christoffersen & Christian Dorion & Kris Jacobs & Lotfi Karoui, 2014. "Nonlinear Kalman Filtering in Affine Term Structure Models," Management Science, INFORMS, vol. 60(9), pages 2248-2268, September.
    12. Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
    13. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    14. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
    15. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    16. Egorov, Alexei V. & Li, Haitao & Ng, David, 2011. "A tale of two yield curves: Modeling the joint term structure of dollar and euro interest rates," Journal of Econometrics, Elsevier, vol. 162(1), pages 55-70, May.
    17. Svetlana Mira & Nicholas Taylor, 2013. "An International Perspective on Risk Management Quality," European Financial Management, European Financial Management Association, vol. 19(5), pages 935-955, November.
    18. Eickholt, Mathias & Entrop, Oliver & Wilkens, Marco, 2014. "Individual investors and suboptimal early exercises in the fixed-income market," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe 14, University of Passau, Faculty of Business and Economics.
    19. Eickholt, Mathias & Entrop, Oliver & Wilkens, Marco, 2018. "What makes individual investors exercise early? Empirical evidence from non-tradable fixed-income products," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 318-334.

  37. Yongmiao Hong & Jun Tu & Guofu Zhou, 2006. "Asymmetries in Stock Returns: Statistical Tests and Economic Evaluation," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1547-1581, 2007 23.

    Cited by:

    1. Westner, Günther & Madlener, Reinhard, 2012. "Investment in new power generation under uncertainty: Benefits of CHP vs. condensing plants in a copula-based analysis," Energy Economics, Elsevier, vol. 34(1), pages 31-44.
    2. Numan Ülkü, 2011. "Modeling Comovement among Emerging Stock Markets: The Case of Budapest and Istanbul," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(3), pages 277-304, July.
    3. Massimo Guidolin & Giovanna Nicodano, 2010. "Ex Post Portfolio Performance with Predictable Skewness and Kurtosis," Carlo Alberto Notebooks 191, Collegio Carlo Alberto.
    4. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    5. Joëts, Marc, 2014. "Energy price transmissions during extreme movements," Economic Modelling, Elsevier, vol. 40(C), pages 392-399.
    6. Lieven Baele & Koen Inghelbrecht, 2005. "Structural versus Temporary Drivers of Country and Industry Risk," International Finance 0511005, University Library of Munich, Germany.
    7. Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    8. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    9. Timothy Falcon Crack & Olivier Ledoit, 2010. "Central limit theorems when data are dependent: addressing the pedagogical gaps," IEW - Working Papers 480, Institute for Empirical Research in Economics - University of Zurich.
    10. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    11. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    12. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.
    13. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
    14. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    15. Nguyen, Quynh Nga & Aboura, Sofiane & Chevallier, Julien & Zhang, Lyuyuan & Zhu, Bangzhu, 2020. "Local Gaussian correlations in financial and commodity markets," European Journal of Operational Research, Elsevier, vol. 285(1), pages 306-323.
    16. Peter Christoffersen & Kris Jacobs & Xisong Jin & Hugues Langlois, 2013. "Dynamic Diversification in Corporate Credit," CREATES Research Papers 2013-46, Department of Economics and Business Economics, Aarhus University.
    17. Immanuel Seidl, 2012. "Markowitz versus Regime Switching: An Empirical Approach," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 033-043, June.
    18. Ying Li & Hossein Kazemi, 2007. "Conditional Properties of Hedge Funds: Evidence from Daily Returns," European Financial Management, European Financial Management Association, vol. 13(2), pages 211-238, March.
    19. Zhichao Zhang & Li Ding & Fan Zhang & Zhuang Zhang, 2015. "Optimal Currency Composition for China's Foreign Reserves: A Copula Approach," The World Economy, Wiley Blackwell, vol. 38(12), pages 1947-1965, December.
    20. Fernando D. Chague, 2013. "Conditional Betas and Investor Uncertainty," Working Papers, Department of Economics 2013_04, University of São Paulo (FEA-USP).
    21. Dahlquist, Magnus & Tédongap, Roméo & Farago, Adam, 2015. "Asymmetries and Portfolio Choice," CEPR Discussion Papers 10706, C.E.P.R. Discussion Papers.
    22. Nguyen, Duc Khuong & Sousa, Ricardo M. & Uddin, Gazi Salah, 2015. "Testing for asymmetric causality between U.S. equity returns and commodity futures returns," Finance Research Letters, Elsevier, vol. 12(C), pages 38-47.
    23. Hsu, Chih-Chiang & Yau, Ruey & Wu, Jyun-Yi, 2009. "Asymmetric Exchange Rate Exposure and Industry Characteristics : Evidence from Japanese Data," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 50(1), pages 57-69, June.
    24. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.
    25. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2020. "Spillovers and co-movements between precious metals and energy markets: Implications on portfolio management," Resources Policy, Elsevier, vol. 69(C).
    26. Gerth, Florian & Temnov, Grigory, 2021. "New Ways of Modeling Loan-to-Income Distributions and their Evolution in Time - A Probability Copula Approach," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 217-236.

  38. Yongmiao Hong & Halbert White, 2005. "Asymptotic Distribution Theory for Nonparametric Entropy Measures of Serial Dependence," Econometrica, Econometric Society, vol. 73(3), pages 837-901, May.

    Cited by:

    1. Song, Haiyan & Wen, Long & Liu, Chang, 2019. "Density tourism demand forecasting revisited," Annals of Tourism Research, Elsevier, vol. 75(C), pages 379-392.
    2. Taoufik Bouezmarni & Abderrahim Taamouti, 2014. "Nonparametric tests for conditional independence using conditional distributions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 697-719, December.
    3. Bouezmarni, Taoufik & Rombouts, Jeroen V. K. & Taamouti, Abderrahim, 2009. "A nonparametric copula based test for conditional independence with applications to granger causality," UC3M Working papers. Economics we093419, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Su, Liangjun & White, Halbert, 2003. "A Consistent Characteristic-Function-Based Test for Conditional Independence," University of California at San Diego, Economics Working Paper Series qt4dv0837f, Department of Economics, UC San Diego.
    5. Zacharias Psaradakis & Marián Vávra, 2019. "Portmanteau tests for linearity of stationary time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 248-262, February.
    6. Fernandes, Marcelo, 2001. "Nonparametric entropy-based tests of independence between stochastic processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 413, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    7. Arthur Lewbel & Susanne M. Schennach, 2003. "A Simple Ordered Data Estimator For Inverse Density Weighted Functions," Boston College Working Papers in Economics 557, Boston College Department of Economics, revised 01 May 2005.
    8. Cui, Liyuan & Hong, Yongmiao & Li, Yingxing, 2021. "Solving Euler equations via two-stage nonparametric penalized splines," Journal of Econometrics, Elsevier, vol. 222(2), pages 1024-1056.
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    24. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "From Blackwell Dominance in Large Samples to Rényi Divergences and Back Again," Econometrica, Econometric Society, vol. 89(1), pages 475-506, January.
    25. Cho, Jin Seo & White, Halbert, 2011. "Generalized runs tests for the IID hypothesis," Journal of Econometrics, Elsevier, vol. 162(2), pages 326-344, June.
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    27. Arthur Lewbel, 2000. "Asymptotic Trimming for Bounded Density Plug-in Estimators," Boston College Working Papers in Economics 479, Boston College Department of Economics, revised 30 Oct 2000.
    28. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
    29. George Kapetanios & Zacharias Psaradakis, 2007. "Semiparametric Sieve-Type GLS Inference in Regressions with Long-Range Dependence," Working Papers 587, Queen Mary University of London, School of Economics and Finance.
    30. Yoon, Gawon, 2010. "Do real exchange rates really follow threshold autoregressive or exponential smooth transition autoregressive models?," Economic Modelling, Elsevier, vol. 27(2), pages 605-612, March.
    31. Herrera Gómez, Marcos & Ruiz Marín, Manuel & Mur Lacambra, Jesús, 2011. "Detección de Dependencia Espacial mediante Análisis Simbólico [Detection of Spatial Dependence using Symbolic Analysis]," MPRA Paper 38603, University Library of Munich, Germany.
    32. Dahl, Christian M. & Nielsen, Steen, 2001. "The Random Walk Of Stock Prices: Implications Of Recent Nonpara-Metric Tests," Working Papers 07-2001, Copenhagen Business School, Department of Economics.
    33. Mariano Matilla-García & Manuel Ruiz Marín, 2010. "A New Test for Chaos and Determinism based on Symbolic Dynamics," Post-Print hal-00911819, HAL.
    34. Wu, Edmond H.C. & Yu, Philip L.H. & Li, W.K., 2009. "A smoothed bootstrap test for independence based on mutual information," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2524-2536, May.
    35. Hong, Yongmiao & Li, Haitao, 2002. "Nonparametric specification testing for continuous-time models with application to spot interest rates," SFB 373 Discussion Papers 2002,32, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    36. Yuri A. Dubnov & Alexandr V. Boulytchev, 2023. "Accelerated Maximum Entropy Method for Time Series Models Estimation," Mathematics, MDPI, vol. 11(18), pages 1-15, September.
    37. Ruiz-Castillo, Javier, 2012. "From the “European Paradox” to a European Drama in citation impact," UC3M Working papers. Economics we1211, Universidad Carlos III de Madrid. Departamento de Economía.
    38. Diks Cees & Panchenko Valentyn, 2008. "Rank-based Entropy Tests for Serial Independence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-21, March.
    39. Yongmiao Hong & Xia Wang & Wenjie Zhang & Shouyang Wang, 2017. "An efficient integrated nonparametric entropy estimator of serial dependence," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 728-780, October.
    40. L. Bagnato & L. De Capitani & A. Punzo, 2016. "The Kullback–Leibler autodependogram," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2574-2594, October.
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  39. Yongmiao Hong & Yoon-Jin Lee, 2005. "Generalized Spectral Tests for Conditional Mean Models in Time Series with Conditional Heteroscedasticity of Unknown Form," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 499-541.

    Cited by:

    1. Ashby, M. & Linton, O. B., 2022. "Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns?," Cambridge Working Papers in Economics 2259, Faculty of Economics, University of Cambridge.
    2. Hamidi Sahneh, Mehdi, 2013. "Testing for Noncausal Vector Autoregressive Representation," MPRA Paper 68867, University Library of Munich, Germany, revised 16 Aug 2014.
    3. Ashby, M. & Linton, O. B., 2022. "Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns?," Janeway Institute Working Papers 2226, Faculty of Economics, University of Cambridge.
    4. Lee, Yoon-Jin, 2014. "Testing a linear dynamic panel data model against nonlinear alternatives," Journal of Econometrics, Elsevier, vol. 178(P1), pages 146-166.
    5. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    6. Escanciano, Juan Carlos & Jacho-Chávez, David T., 2010. "Approximating the critical values of Cramér-von Mises tests in general parametric conditional specifications," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 625-636, March.
    7. Yoon-Jin Lee & Yongmiao Hong, 2004. "Specification Testing for Multivariate Time Series Volatility Models," Econometric Society 2004 Far Eastern Meetings 696, Econometric Society.
    8. Hamidi Sahneh, Mehdi, 2015. "Are the shocks obtained from SVAR fundamental?," MPRA Paper 65126, University Library of Munich, Germany.
    9. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    10. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    11. Escanciano, Juan Carlos & Velasco, Carlos, 2003. "Generalized spectral tests for the martingale difference hypothesis," DES - Working Papers. Statistics and Econometrics. WS ws035312, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Jarrow, Robert & Kwok, Simon, 2013. "Specification Tests of Calibrated Option Pricing Models," Working Papers 2013-08, University of Sydney, School of Economics, revised Dec 2014.
    13. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    14. Peter C.B. Phillips & Sainan Jin, 2013. "Testing the Martingale Hypothesis," Cowles Foundation Discussion Papers 1912, Cowles Foundation for Research in Economics, Yale University.
    15. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.
    16. Xuexin WANG, 2021. "Generalized Spectral Tests for High Dimensional Multivariate Martingale Difference Hypotheses," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    17. Gao, Jiti & Hong, Yongmiao, 2007. "Central limit theorems for weighted quadratic forms of dependent processes with applications in specification testing," MPRA Paper 11977, University Library of Munich, Germany, revised Dec 2007.
    18. Bin Chen & Jinho Choi & Juan Carlos Escanciano, 2015. "Testing for Fundamental Vector Moving Average Representations," CAEPR Working Papers 2015-022, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    19. Péter Farkas, 2013. "Counting Process Generated by Boundary-crossing Events. Theory and Statistical Applications," CEU Working Papers 2013_4, Department of Economics, Central European University.
    20. Christian Gouriéroux & Joann Jasiak, 2016. "Robust Analysis of the Martingale Hypothesis," Working Papers 2016-18, Center for Research in Economics and Statistics.
    21. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    22. Mengya Liu & Fukan Zhu & Ke Zhu, 2020. "Multi-frequency-band tests for white noise under heteroskedasticity," Papers 2004.09161, arXiv.org.
    23. Karim M. Abadir & Gabriel Talmain, 2008. "Macro and Financial Markets: The Memory of an Elephant?," Working Paper series 17_08, Rimini Centre for Economic Analysis.
    24. Lim, Kian-Ping & Brooks, Robert D. & Hinich, Melvin J., 2008. "Nonlinear serial dependence and the weak-form efficiency of Asian emerging stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 527-544, December.
    25. Juan Carlos Escanciano, 2005. "Goodness-of-fit Tests for Linear and Non-linear Time Series Models," Faculty Working Papers 02/05, School of Economics and Business Administration, University of Navarra.
    26. Kian-Ping Lim & Weiwei Luo & Jae H. Kim, 2013. "Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests," Applied Economics, Taylor & Francis Journals, vol. 45(8), pages 953-962, March.
    27. Hill Jonathan B., 2013. "Stochastically weighted average conditional moment tests of functional form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(2), pages 121-139, April.
    28. Lim, Kian-Ping & Brooks, Robert D. & Kim, Jae H., 2008. "Financial crisis and stock market efficiency: Empirical evidence from Asian countries," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 571-591, June.
    29. Escanciano, J. Carlos & Velasco, Carlos, 2006. "Testing the martingale difference hypothesis using integrated regression functions," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2278-2294, December.
    30. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers 29/14, Institute for Fiscal Studies.
    31. Semei Coronado-Ram'irez & Pedro Celso-Arellano & Omar Rojas, 2014. "Adaptive Market Efficiency of Agricultural Commodity Futures Contracts," Papers 1412.8017, arXiv.org, revised Mar 2015.
    32. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1), pages 27-35.
    33. Zhang, Bing, 2013. "Are the crude oil markets becoming more efficient over time? New evidence from a generalized spectral test," Energy Economics, Elsevier, vol. 40(C), pages 875-881.
    34. Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023. "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, vol. 235(2), pages 972-1000.
    35. Donghang Luo & Ke Zhu & Huan Gong & Dong Li, 2020. "Testing error distribution by kernelized Stein discrepancy in multivariate time series models," Papers 2008.00747, arXiv.org.
    36. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
    37. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into Multivariate Variance Ratio Statistics and their application to Stock Market Predictability," Cambridge Working Papers in Economics 1552, Faculty of Economics, University of Cambridge.
    38. Hong, Yongmiao & Lin, Hai & Wu, Chunchi, 2012. "Are corporate bond market returns predictable?," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2216-2232.
    39. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers CWP29/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    40. McPherson, Matthew Q. & Palardy, Joseph, 2007. "Are international stock returns predictable?: An examination of linear and non-linear predictability using generalized spectral tests," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(5), pages 452-464, December.
    41. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
    42. Herman J. Bierens & Li Wang, 2017. "Weighted simulated integrated conditional moment tests for parametric conditional distributions of stationary time series processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 103-135, March.
    43. Song, Zhaogang, 2011. "A martingale approach for testing diffusion models based on infinitesimal operator," Journal of Econometrics, Elsevier, vol. 162(2), pages 189-212, June.
    44. Juan Carlos Escanciano, 2006. "Joint Diagnostic Tests for Conditional Mean and Variance Specifications," Faculty Working Papers 02/06, School of Economics and Business Administration, University of Navarra.
    45. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into multivariate variance ratio statistics and their application to stock market predictability," CeMMAP working papers 13/15, Institute for Fiscal Studies.
    46. Wasel Shadat, 2011. "On the Nonparametric Tests of Univariate GARCH Regression Models," Economics Discussion Paper Series 1115, Economics, The University of Manchester.
    47. Michael William Ashby & Oliver Bruce Linton, 2024. "Do Consumption-Based Asset Pricing Models Explain the Dynamics of Stock Market Returns?," JRFM, MDPI, vol. 17(2), pages 1-42, February.
    48. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.
    49. Kugiumtzis Dimitris, 2008. "Evaluation of Surrogate and Bootstrap Tests for Nonlinearity in Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-26, March.
    50. Karim M. Abadir & Gabriel Talmain, 2012. "Beyond Co-Integration: Modelling Co-Movements in Macro finance," Working Paper series 25_12, Rimini Centre for Economic Analysis.

  40. Yongmiao Hong, 2005. "Nonparametric Specification Testing for Continuous-Time Models with Applications to Term Structure of Interest Rates," The Review of Financial Studies, Society for Financial Studies, vol. 18(1), pages 37-84.

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    1. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    2. Tae-Hwy Lee & Weiping Yang, 2014. "Granger-Causality in Quantiles between Financial Markets: Using Copula Approach," Working Papers 201406, University of California at Riverside, Department of Economics.
    3. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    4. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Inference for Integrated Volatility," Departmental Working Papers 200616, Rutgers University, Department of Economics.
    5. Yayi Yan & Jiti Gao & Bin Peng, 2021. "On Time-Varying VAR Models: Estimation, Testing and Impulse Response Analysis," Papers 2111.00450, arXiv.org.
    6. Jumbe, George, 2023. "Credit Risk Assessment Using Default Models: A Review," OSF Preprints ksb8n, Center for Open Science.
    7. Almeida, Caio & Ardison, Kym & Kubudi, Daniela, 2014. "Approximating Risk Premium on a Parametric Arbitrage-free Term Structure Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    8. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    9. Gao, Jiti & Casas, Isabel, 2006. "Specification testing in discretized diffusion models: Theory and practice," MPRA Paper 11980, University Library of Munich, Germany, revised Aug 2007.
    10. Bu, Ruijun & Hadri, Kaddour & Kristensen, Dennis, 2021. "Diffusion copulas: Identification and estimation," Journal of Econometrics, Elsevier, vol. 221(2), pages 616-643.
    11. Al-Zoubi, Haitham A., 2019. "Bond and option prices with permanent shocks," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 272-290.
    12. Igor L. Kheifets, 2015. "Specification tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 67-94, February.
    13. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    14. Cui, Liyuan & Hong, Yongmiao & Li, Yingxing, 2021. "Solving Euler equations via two-stage nonparametric penalized splines," Journal of Econometrics, Elsevier, vol. 222(2), pages 1024-1056.
    15. Zaichao Du, 2009. "Nonparametric Bootstrap Tests for Independence of Generalized Errors," CAEPR Working Papers 2009-023, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    16. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    17. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    18. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    19. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    20. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    21. Robert A. Jarrow, 2009. "The Term Structure of Interest Rates," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 69-96, November.
    22. Xibin Zhang & Robert D. Brooks & Maxwell L. King, 2007. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics.
    23. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    24. Michael B. Gordy & Alexander J. McNeil, 2018. "Spectral Backtests of Forecast Distributions with Application to Risk Management," Finance and Economics Discussion Series 2018-021, Board of Governors of the Federal Reserve System (U.S.).
    25. Aït-Sahalia, Yacine & Park, Joon Y., 2012. "Stationarity-based specification tests for diffusions when the process is nonstationary," Journal of Econometrics, Elsevier, vol. 169(2), pages 279-292.
    26. Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.
    27. Péter Farkas, 2013. "Counting Process Generated by Boundary-crossing Events. Theory and Statistical Applications," CEU Working Papers 2013_4, Department of Economics, Central European University.
    28. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    29. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    30. Igor Kheifets, 2011. "Goodness-of-fit testing (in Russian)," Quantile, Quantile, issue 9, pages 25-34, July.
    31. Ergun A. Tolga & Jun Jongbyung, 2010. "Conditional Skewness, Kurtosis, and Density Specification Testing: Moment-Based versus Nonparametric Tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-21, September.
    32. Veronika Czellar & G. Andrew Karolyi & Elvezio Ronchetti, 2007. "Indirect robust estimation of the short-term interest rate process," Post-Print hal-00463251, HAL.
    33. Philippe Lambert & Sébastien Laurent & David Veredas, 2012. "Testing conditional asymmetry. A residual based approach," ULB Institutional Repository 2013/136195, ULB -- Universite Libre de Bruxelles.
    34. Xu, Ke-Li, 2009. "Empirical likelihood-based inference for nonparametric recurrent diffusions," Journal of Econometrics, Elsevier, vol. 153(1), pages 65-82, November.
    35. Corradi, Valentina & Swanson, Norman R., 2011. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Journal of Econometrics, Elsevier, vol. 161(2), pages 304-324, April.
    36. Fan, Jianqing & Fan, Yingying & Jiang, Jiancheng, 2007. "Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 618-631, June.
    37. Yu, Jun, 2012. "Bias in the estimation of the mean reversion parameter in continuous time models," Journal of Econometrics, Elsevier, vol. 169(1), pages 114-122.
    38. Zhang, Dongna & Chen, Xihui Haviour & Lau, Chi Keung Marco & Xu, Bing, 2023. "Implications of cryptocurrency energy usage on climate change," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    39. Bouri, Elie & Gupta, Rangan & Lau, Chi Keung Marco & Roubaud, David & Wang, Shixuan, 2018. "Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 297-307.
    40. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    41. Mancini, Cecilia & Renò, Roberto, 2011. "Threshold estimation of Markov models with jumps and interest rate modeling," Journal of Econometrics, Elsevier, vol. 160(1), pages 77-92, January.
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    43. Juan Carlos Escanciano & Zaichao Du, 2015. "Backtesting Expected Shortfall: Accounting for Tail Risk," CAEPR Working Papers 2015-001, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
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    85. Aman Ullah & Yong Bao & Yun Wang, 2014. "Exact Distribution of the Mean Reversion Estimator in the Ornstein-Uhlenbeck Process," Working Papers 201413, University of California at Riverside, Department of Economics.
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    94. Al-Zoubi, Haitham A., 2009. "Short-term spot rate models with nonparametric deterministic drift," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 731-747, August.
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  41. Yongmiao Hong & Haitao Li & Feng Zhao, 2004. "Out-of-Sample Performance of Discrete-Time Spot Interest Rate Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 457-473, October.

    Cited by:

    1. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    2. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    3. Geweke, John & Amisano, Gianni, 2010. "Comparing and evaluating Bayesian predictive distributions of asset returns," International Journal of Forecasting, Elsevier, vol. 26(2), pages 216-230, April.
    4. Hitesh Doshi & Kris Jacobs & Rui Liu, 2021. "Information in the Term Structure: A Forecasting Perspective," Management Science, INFORMS, vol. 67(8), pages 5255-5277, August.
    5. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    6. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    8. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    9. Tianshun Yan & Yanyong Zhao & Wentao Wang, 2020. "Likelihood-based estimation of a semiparametric time-dependent jump diffusion model of the short-term interest rate," Computational Statistics, Springer, vol. 35(2), pages 539-557, June.
    10. Emrah Ismail Cevik & Sel Dibooglu & Atif Awad Abdallah & Eisa Abdulrahman Al-Eisa, 2021. "Oil prices, stock market returns, and volatility spillovers: evidence from Saudi Arabia," International Economics and Economic Policy, Springer, vol. 18(1), pages 157-175, February.
    11. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    12. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    13. Muteba Mwamba, John & Thabo, Lethaba & Uwilingiye, Josine, 2014. "Modelling the short-term interest rate with stochastic differential equation in continuous time: linear and nonlinear models," MPRA Paper 64386, University Library of Munich, Germany.
    14. M. Rypdal & O. L{o}vsletten, 2011. "Multifractal modeling of short-term interest rates," Papers 1111.5265, arXiv.org.
    15. Kam Fong Chan, 2005. "Modelling conditional heteroscedasticity and jumps in Australian short‐term interest rates," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(4), pages 537-551, December.
    16. Hong, Yongmiao & Lin, Hai & Wang, Shouyang, 2010. "Modeling the dynamics of Chinese spot interest rates," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1047-1061, May.
    17. Valentina Corradi & Norman R. Swanson, 2003. "Bootstrap Specification Tests for Diffusion Processes," Departmental Working Papers 200321, Rutgers University, Department of Economics.
    18. Cai, Lili & Swanson, Norman R., 2011. "In- and out-of-sample specification analysis of spot rate models: Further evidence for the period 1982-2008," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 743-764, September.
    19. Manzan, Sebastiano & Zerom, Dawit, 2008. "A bootstrap-based non-parametric forecast density," International Journal of Forecasting, Elsevier, vol. 24(3), pages 535-550.
    20. Yun, Jaeho, 2014. "Out-of-sample density forecasts with affine jump diffusion models," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 74-87.
    21. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173.
    22. Dai, Zhifeng & Tang, Rui & Zhang, Xinhua, 2023. "Multilayer network analysis for measuring the inter-connectedness between the oil market and G20 stock markets," Energy Economics, Elsevier, vol. 120(C).
    23. Bali, Turan G. & Wu, Liuren, 2006. "A comprehensive analysis of the short-term interest-rate dynamics," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1269-1290, April.
    24. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
    25. Li, Shaoyu & Zheng, Tingguo, 2017. "Modeling spot rate using a realized stochastic volatility model with level effect and dynamic drift☆," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 200-221.
    26. Koray Yıldırım & Neşe Algan & Harun Bal, 2024. "Investment Hysteresis: An Empirical Essay Turkish Case," Evaluation Review, , vol. 48(1), pages 143-176, February.
    27. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.
    28. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    29. Al-Zoubi, Haitham A., 2009. "Short-term spot rate models with nonparametric deterministic drift," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 731-747, August.
    30. Bayraci, Selcuk & UNAL, GAZANFER, 2010. "Continuous time modeling of interest rates: An empirical study on the Turkish short rate," MPRA Paper 28091, University Library of Munich, Germany.
    31. Bhardwaj, Geetesh & Corradi, Valentina & Swanson, Norman R., 2008. "A Simulation-Based Specification Test for Diffusion Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 176-193, April.
    32. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    33. Dai, Zhifeng & Tang, Rui & Zhang, Xiaotong, 2023. "A new multilayer network for measuring interconnectedness among the energy firms," Energy Economics, Elsevier, vol. 124(C).

  42. Yongmiao Hong & Chihwa Kao, 2004. "Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models," Econometrica, Econometric Society, vol. 72(5), pages 1519-1563, September.
    See citations under working paper version above.
  43. Yongmiao Hong & Tae-Hwy Lee, 2003. "Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1048-1062, November.

    Cited by:

    1. Zongwu Cai, 2013. "Functional Coefficient Models for Economic and Financial Data," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    2. Andrea Bastianin & Matteo Manera, 2020. "A test of time reversibility based on Lmoments with an application to the business cycles of the G7 economies," Working Papers 445, University of Milano-Bicocca, Department of Economics, revised Jun 2020.
    3. Marcus F. da Silva & Eder Johnson de Area Leão Pereira & Idaraí Santos de Santana & José Garcia Vivas Miranda, 2013. "Pattern of fluctuations in the exchange rate change from fixed to floating, in Brazil, Argentina and Mexico," Economics Bulletin, AccessEcon, vol. 33(2), pages 1547-1555.
    4. Carlo Altavilla & Matteo Ciccarelli, 2006. "Inflation Forecasts, Monetary Policy and Unemployment Dynamics: Evidence from the US and the Euro Area," Discussion Papers 7_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    5. Costantini, Mauro & Cuaresma, Jesus Crespo & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Economics Series 305, Institute for Advanced Studies.
    6. Zdeněk Hlávka & Marie Hušková & Claudia Kirch & Simos G. Meintanis, 2017. "Fourier--type tests involving martingale difference processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 468-492, April.
    7. Manish Kumar, 2010. "Modelling Exchange Rate Returns Using Non-linear Models," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(1), pages 101-125, January.
    8. Roch, Oriol, 2013. "Histogram-based prediction of directional price relatives," Finance Research Letters, Elsevier, vol. 10(3), pages 110-115.
    9. Escanciano, Juan Carlos & Velasco, Carlos, 2003. "Generalized spectral tests for the martingale difference hypothesis," DES - Working Papers. Statistics and Econometrics. WS ws035312, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
    11. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    12. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    13. Peter C.B. Phillips & Sainan Jin, 2013. "Testing the Martingale Hypothesis," Cowles Foundation Discussion Papers 1912, Cowles Foundation for Research in Economics, Yale University.
    14. Carlo Altavilla & Paul De Grauwe, 2006. "Forecasting and Combining Competing Models of Exchange Rate Determination," CESifo Working Paper Series 1747, CESifo.
    15. Rahimi, Fatemeh & Mousavian Anaraki, Seyed Alireza, 2020. "Proposing an Innovative Model Based on the Sierpinski Triangle for Forecasting EUR/USD Direction Changes," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(4), pages 423-444, October.
    16. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    17. García Ruiz Reyna Susana & Cruz Aké Salvador & Venegas Martínez Francisco, 2014. "Una medida de eficiencia de mercado: Un enfoque de teoría de la información," Contaduría y Administración, Accounting and Management, vol. 59(4), pages 137-166, octubre-d.
    18. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
    19. Guo, Hui & Savickas, Robert, 2008. "Forecasting foreign exchange rates using idiosyncratic volatility," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1322-1332, July.
    20. Kiani, Khurshid M., 2013. "Can signal extraction help predict risk premia in foreign exchange rates," Economic Modelling, Elsevier, vol. 33(C), pages 926-939.
    21. Pippenger, John, 2012. "The Fragility of Overshooting," University of California at Santa Barbara, Economics Working Paper Series qt4rd5j98c, Department of Economics, UC Santa Barbara.
    22. Kirstin Hubrich & Kenneth D. West, 2008. "Forecast Evaluation of Small Nested Model Sets," NBER Working Papers 14601, National Bureau of Economic Research, Inc.
    23. Xuexin WANG, 2021. "Generalized Spectral Tests for High Dimensional Multivariate Martingale Difference Hypotheses," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    24. Todd E. Clark & Michael W. Mccracken, 2014. "Tests Of Equal Forecast Accuracy For Overlapping Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 415-430, April.
    25. Zongwu Cai & Qi Li, 2013. "Nonparametric Estimation Of Varying Coefficient Dynamic Panel Data Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    26. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    27. Firat Melih Yilmaz & Ozer Arabaci, 2021. "Should Deep Learning Models be in High Demand, or Should They Simply be a Very Hot Topic? A Comprehensive Study for Exchange Rate Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 217-245, January.
    28. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    29. Cai, Zongwu & Xu, Xiaoping, 2008. "Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1595-1608.
    30. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
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    32. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2023. "Optimal Local Model Averaging for Divergent-Dimensional Functional-Coefficient Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202309, University of Kansas, Department of Economics, revised Sep 2023.
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    34. PREMINGER, Arie & FRANCK, Raphael, 2007. "Forecasting exchange rates: a robust regression approach," LIDAM Reprints CORE 1917, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Pippenger, John, 2008. "Freely Floating Exchange Rates Do Not Systematically Overshoot," University of California at Santa Barbara, Economics Working Paper Series qt97m8z6hw, Department of Economics, UC Santa Barbara.
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    37. Irina Murtazashvili & Di Liu & Artem Prokhorov, 2015. "Two‐sample nonparametric estimation of intergenerational income mobility in the United States and Sweden," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(5), pages 1733-1761, December.
    38. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    39. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
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    41. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    42. Altavilla, Carlo & Ciccarelli, Matteo, 2010. "Evaluating the effect of monetary policy on unemployment with alternative inflation forecasts," Economic Modelling, Elsevier, vol. 27(1), pages 237-253, January.
    43. Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
    44. Escanciano, J. Carlos & Velasco, Carlos, 2006. "Testing the martingale difference hypothesis using integrated regression functions," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2278-2294, December.
    45. Cai, Zongwu & Hong, Yongmiao, 2003. "Nonparametric Methods in Continuous-Time Finance: A Selective Review," SFB 373 Discussion Papers 2003,15, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    46. McCracken, Michael W., 2004. "Parameter estimation and tests of equal forecast accuracy between non-nested models," International Journal of Forecasting, Elsevier, vol. 20(3), pages 503-514.
    47. Adeyeye Patrick Olufemi & Aluko Olufemi Adewale & Migiro Stephen Oseko, 2017. "Efficiency of Foreign Exchange Markets in Sub-Saharan Africa in the Presence of Structural Break: A Linear and Non-Linear Testing Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 9(4), pages 122-131.
    48. Massimo Guidolin & Francesco Chincoli, 2017. "Linear and Nonlinear Predictability in Investment Style Factors: Multivariate Evidence," BAFFI CAREFIN Working Papers 1754, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    49. Haiqiang Chen & Terence Chong & Jushan Bai, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," Econometric Reviews, Taylor & Francis Journals, vol. 31(2), pages 142-170.
    50. Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 383-406, November.
    51. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1), pages 27-35.
    52. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Miranda, José G.V. & García-Rubio, Raquel, 2013. "How fast do stock prices adjust to market efficiency? Evidence from a detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1631-1637.
    53. Cai, Zongwu & Das, Mitali & Xiong, Huaiyu & Wu, Xizhi, 2006. "Functional coefficient instrumental variables models," Journal of Econometrics, Elsevier, vol. 133(1), pages 207-241, July.
    54. Juan Carlos Escanciano, 2005. "On the Asymptotic Power Properties of Specification Tests for Dynamic Parametric Regressions," Faculty Working Papers 07/05, School of Economics and Business Administration, University of Navarra.
    55. McPherson, Matthew Q. & Palardy, Joseph, 2007. "Are international stock returns predictable?: An examination of linear and non-linear predictability using generalized spectral tests," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(5), pages 452-464, December.
    56. Moura, Marcelo L. & Lima, Adauto R. S., 2007. "Empirical exchange rate models fit: Evidence from the Brazilian economy," Insper Working Papers wpe_87, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    57. Yang, Jian & Su, Xiaojing & Kolari, James W., 2008. "Do Euro exchange rates follow a martingale? Some out-of-sample evidence," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 729-740, May.
    58. Cai, Zongwu, 2003. "Trending Time-Varying Coefficient Models With Serially Correlated Errors," SFB 373 Discussion Papers 2003,7, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    59. Al-Khazali, Osamah M. & Pyun, Chong Soo & Kim, Daewon, 2012. "Are exchange rate movements predictable in Asia-Pacific markets? Evidence of random walk and martingale difference processes," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 221-231.
    60. Moura, Marcelo L. , & Lima, Adauto R. S. & Mendonça, Rodrigo M., 2008. "Exchange Rate and Fundamentals: The Case of Brazil," Insper Working Papers wpe_114, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    61. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    62. Zongwu Cai & Henong Li, 2013. "Convergency and Divergency of Functional Coefficient Weak Instrumental Variables Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    63. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    64. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    65. Manish KUMAR, 2009. "Exploiting The Information Of Stock Market To Forecast Exchange Rate Movements," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 563-575, November.

  44. Hong, Yongmiao & Lee, Tae-Hwy, 2003. "Diagnostic Checking For The Adequacy Of Nonlinear Time Series Models," Econometric Theory, Cambridge University Press, vol. 19(6), pages 1065-1121, December.

    Cited by:

    1. Chen, Min & Zhu, Ke, 2015. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," Journal of Econometrics, Elsevier, vol. 189(2), pages 313-320.
    2. Escanciano, Juan Carlos & Jacho-Chávez, David T., 2010. "Approximating the critical values of Cramér-von Mises tests in general parametric conditional specifications," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 625-636, March.
    3. Zacharias Psaradakis & Marián Vávra, 2019. "Portmanteau tests for linearity of stationary time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 248-262, February.
    4. Tae-Hwy Lee & Yong Bao & Burak Saltoğlu, 2007. "Comparing density forecast models Previous versions of this paper have been circulated with the title, 'A Test for Density Forecast Comparison with Applications to Risk Management' since October 2003;," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 203-225.
    5. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.
    6. Wang, Xuqin & Li, Muyi, 2023. "Bootstrapping the transformed goodness-of-fit test on heavy-tailed GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 184(C).
    7. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.
    8. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    9. Meitz, Mika & Teräsvirta, Timo, 2004. "Evaluating models of autoregressive conditional duration," SSE/EFI Working Paper Series in Economics and Finance 557, Stockholm School of Economics, revised 13 Dec 2004.
    10. Philippe Lambert & Sébastien Laurent & David Veredas, 2012. "Testing conditional asymmetry. A residual based approach," ULB Institutional Repository 2013/136195, ULB -- Universite Libre de Bruxelles.
    11. Escanciano, J. Carlos, 2010. "Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series Models," Econometric Theory, Cambridge University Press, vol. 26(3), pages 744-773, June.
    12. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    13. Chen, Min & Zhu, Ke, 2013. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," MPRA Paper 50487, University Library of Munich, Germany.
    14. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    15. Carlos Escanciano, J., 2008. "Joint and marginal specification tests for conditional mean and variance models," Journal of Econometrics, Elsevier, vol. 143(1), pages 74-87, March.
    16. Juan Carlos Escanciano, 2005. "Goodness-of-fit Tests for Linear and Non-linear Time Series Models," Faculty Working Papers 02/05, School of Economics and Business Administration, University of Navarra.
    17. Gloria González-Rivera & Tae-Hwy Lee & Santosh Mishra, 2008. "Jumps in cross-sectional rank and expected returns: a mixture model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 585-606.
    18. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    19. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
    20. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    21. Juan Carlos Escanciano, 2006. "Joint Diagnostic Tests for Conditional Mean and Variance Specifications," Faculty Working Papers 02/06, School of Economics and Business Administration, University of Navarra.
    22. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    23. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    24. Wasel Shadat, 2011. "On the Nonparametric Tests of Univariate GARCH Regression Models," Economics Discussion Paper Series 1115, Economics, The University of Manchester.
    25. M. Dolores Jiménez-Gamero & Sangyeol Lee & Simos G. Meintanis, 2020. "Goodness-of-fit tests for parametric specifications of conditionally heteroscedastic models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 682-703, September.

  45. Yongmiao Hong, 2001. "Testing for Independence between Two stationary Time Series via the Empirical Characteristic Function," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 123-164, May.

    Cited by:

    1. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    2. Chu, Ba, 2023. "A distance-based test of independence between two multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 195(C).

  46. Hong, Yongmiao & Lee, Jin, 2001. "One-Sided Testing For Arch Effects Using Wavelets," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1051-1081, December.

    Cited by:

    1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    2. Francq, Christian & Zakoïan, Jean-Michel, 2009. "Testing the Nullity of GARCH Coefficients: Correction of the Standard Tests and Relative Efficiency Comparisons," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 313-324.
    3. Li, Linyuan & Yao, Shan & Duchesne, Pierre, 2014. "On wavelet-based testing for serial correlation of unknown form using Fan’s adaptive Neyman method," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 308-327.
    4. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.
    5. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    6. Gencay, Ramazan & Fan, Yanqin, 2007. "Unit Root Tests with Wavelets," MPRA Paper 9832, University Library of Munich, Germany.
    7. Yousefi, Shahriar & Weinreich, Ilona & Reinarz, Dominik, 2005. "Wavelet-based prediction of oil prices," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 265-275.
    8. Christian Francq & Jean-Michel Zakoïan, 2006. "Inference in GARCH when some coefficients are equal to zero," Computing in Economics and Finance 2006 64, Society for Computational Economics.
    9. Ho, Kin Yip & Tsui, Albert K.C., 2004. "Analysis of real GDP growth rates of greater China: An asymmetric conditional volatility approach," China Economic Review, Elsevier, vol. 15(4), pages 424-442.
    10. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
    11. Zhou, Yong & Wan, Alan T.K. & Xie, Shangyu & Wang, Xiaojing, 2010. "Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 183-201, November.
    12. Kin-Yip Ho & Albert K. Tsui & Zhaoyong Zhang, 2013. "Conditional Volatility Asymmetry Of Business Cycles: Evidence From Four Oecd Countries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(3), pages 33-56, September.

  47. Lee, Jin & Hong, Yongmiao, 2001. "Testing For Serial Correlation Of Unknown Form Using Wavelet Methods," Econometric Theory, Cambridge University Press, vol. 17(2), pages 386-423, April.

    Cited by:

    1. Hafner, Christian, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," LIDAM Reprints ISBA 2012027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Li, Linyuan & Yao, Shan & Duchesne, Pierre, 2014. "On wavelet-based testing for serial correlation of unknown form using Fan’s adaptive Neyman method," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 308-327.
    3. Ramazan Gencay & Nikola Gradojevic, 2009. "Errors-in-Variables Estimation with No Instruments," Working Paper series 30_09, Rimini Centre for Economic Analysis.
    4. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.
    5. Gencay, Ramazan & Fan, Yanqin, 2007. "Unit Root Tests with Wavelets," MPRA Paper 9832, University Library of Munich, Germany.
    6. Mengya Liu & Fukan Zhu & Ke Zhu, 2020. "Multi-frequency-band tests for white noise under heteroskedasticity," Papers 2004.09161, arXiv.org.
    7. Antonio Cosma & Olivier Scaillet & Rainer von Sachs, 2005. "Multiariate Wavelet-based sahpe preserving estimation for dependant observation," FAME Research Paper Series rp144, International Center for Financial Asset Management and Engineering.
    8. Yousefi, Shahriar & Weinreich, Ilona & Reinarz, Dominik, 2005. "Wavelet-based prediction of oil prices," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 265-275.
    9. Fabio S. Dias & Gareth W. Peters, 2020. "A Non-parametric Test and Predictive Model for Signed Path Dependence," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 461-498, August.
    10. Xiao, Han & Wu, Wei Biao, 2019. "Portmanteau Test and Simultaneous Inference for Serial Covariances," IRTG 1792 Discussion Papers 2019-017, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Yushu Li & Fredrik N. G. Andersson, 2021. "A simple wavelet-based test for serial correlation in panel data models," Empirical Economics, Springer, vol. 60(5), pages 2351-2363, May.
    12. Duchesne, Pierre & Li, Linyuan & Vandermeerschen, Jill, 2010. "On testing for serial correlation of unknown form using wavelet thresholding," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2512-2531, November.
    13. Gençay, Ramazan & Signori, Daniele, 2015. "Multi-scale tests for serial correlation," Journal of Econometrics, Elsevier, vol. 184(1), pages 62-80.
    14. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    15. Kim, Sangbae & In, Francis, 2005. "The relationship between stock returns and inflation: new evidence from wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 435-444, June.
    16. Stelios Bekiros, 2014. "Timescale Analysis with an Entropy-Based Shift-Invariant Discrete Wavelet Transform," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 231-251, August.
    17. Zhou, Yong & Wan, Alan T.K. & Xie, Shangyu & Wang, Xiaojing, 2010. "Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 183-201, November.
    18. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, December.
    19. Sharif Md. Raihan & Yi Wen & Bing Zeng, 2005. "Wavelet: a new tool for business cycle analysis," Working Papers 2005-050, Federal Reserve Bank of St. Louis.
    20. Li, Linyuan & Duchesne, Pierre & Liou, Chu Pheuil, 2021. "On diagnostic checking in ARMA models with conditionally heteroscedastic martingale difference using wavelet methods," Econometrics and Statistics, Elsevier, vol. 19(C), pages 169-187.

  48. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.

    Cited by:

    1. Tae-Hwy Lee & Weiping Yang, 2014. "Granger-Causality in Quantiles between Financial Markets: Using Copula Approach," Working Papers 201406, University of California at Riverside, Department of Economics.
    2. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
    3. Tam Hoang-Nhat Dang & Nhan Thien Nguyen & Duc Hong Vo, 2023. "Sectoral volatility spillovers and their determinants in Vietnam," Economic Change and Restructuring, Springer, vol. 56(1), pages 681-700, February.
    4. Jung-Bin Su, 2022. "The Research on the Interactions between the Emerging and Developed Markets: From Region and Structural Break Perspectives," Mathematics, MDPI, vol. 10(8), pages 1-38, April.
    5. Manish Kumar, 2011. "Return and volatility spillovers: evidence from Indian exchange rates," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 3(4), pages 371-387.
    6. Rangan Gupta & Sowmya Subramaniam & Elie Bouri & Qiang Ji, 2020. "Infectious Disease-Related Uncertainty and the Safe-Haven Characteristic of US Treasury Securities," Working Papers 202078, University of Pretoria, Department of Economics.
    7. Michael McAleer & Kim Radalj, 2013. "Herding, Information Cascades and Volatility Spillovers in Futures Markets," Journal of Reviews on Global Economics, Lifescience Global, vol. 2, pages 307-329.
    8. Marcin Faldzinski & Magdalena Osinska, 2016. "Volatility estimators in econometric analysis of risk transfer on capital markets," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 21-35.
    9. Xue-Zhong He & Kai Li & Chuncheng Wang, 2018. "Time-varying economic dominance in financial markets: A bistable dynamics approach," Published Paper Series 2018-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    10. Ahmed Shamiri & Abu Hassan, 2005. "Modeling and Forecasting Volatility of the Malaysian and the Singaporean stock indices using Asymmetric GARCH models and Non-normal Densities," Econometrics 0509015, University Library of Munich, Germany.
    11. Eduard Baumohl & Evzen Kocenda & Stefan Lyocsa & Tomas Vyrost, 2016. "Networks of volatility spillovers among stock markets," KIER Working Papers 941, Kyoto University, Institute of Economic Research.
    12. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    13. Pablo Mendieta Ossio & Sergio Cerezo Aguirre & Javier Cossío Medinacelli, 2009. "¿La inflación está de vuelta en Sudamérica?. Choques exógenos, expectativas y credibilidad de la política monetaria," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 11(1), pages 111-146, December.
    14. Dilip Kumar & S. Maheswaran, 2013. "Return, Volatility and Risk Spillover from Oil Prices and the US Dollar Exchange Rate to the Indian Industrial Sectors," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(1), pages 61-91, February.
    15. Lyócsa, Štefan, 2014. "Growth-returns nexus: Evidence from three Central and Eastern European countries," Economic Modelling, Elsevier, vol. 42(C), pages 343-355.
    16. Dilip Kumar, 2017. "A Study of Risk Spillover in the Crude Oil and the Natural Gas Markets," Global Business Review, International Management Institute, vol. 18(6), pages 1465-1477, December.
    17. Yoon-Jin Lee & Yongmiao Hong, 2004. "Specification Testing for Multivariate Time Series Volatility Models," Econometric Society 2004 Far Eastern Meetings 696, Econometric Society.
    18. Saban Nazlioglu & Shawkat Hammoudeh & Rangan Gupta, 2013. "Volatility Transmission between Islamic and Conventional Equity Markets: Evidence from Causality-in-Variance Test," Working Papers 201384, University of Pretoria, Department of Economics.
    19. Jianxin Wang, 2007. "Foreign Ownership and Volatility Dynamics of Indonesian Stocks," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 201-210, September.
    20. Jin Guo & Tetsuji Tanaka, 2019. "Determinants of international price volatility transmissions: the role of self-sufficiency rates in wheat-importing countries," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-13, December.
    21. Nazlioglu, Saban & Gormus, N. Alper & Soytas, Uğur, 2016. "Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis," Energy Economics, Elsevier, vol. 60(C), pages 168-175.
    22. Yıldırım, Durmuş Çağrı & Cevik, Emrah Ismail & Esen, Ömer, 2020. "Time-varying volatility spillovers between oil prices and precious metal prices," Resources Policy, Elsevier, vol. 68(C).
    23. Fiona Tregenna & Kabeya C. Mulamba, 2019. "Spatial dependence of per capita property tax income in South Africa," Working Papers 202, Economic Research Southern Africa.
    24. Grydaki, Maria & Bezemer, Dirk J., 2012. "The Role of Credit in Great Moderation: a Multivariate GARCH Approach," MPRA Paper 39813, University Library of Munich, Germany.
    25. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    26. Bouri, Elie & Awartani, Basel & Maghyereh, Aktham, 2016. "Crude oil prices and sectoral stock returns in Jordan around the Arab uprisings of 2010," Energy Economics, Elsevier, vol. 56(C), pages 205-214.
    27. Xu, Haifeng & Hamori, Shigeyuki, 2012. "Dynamic linkages of stock prices between the BRICs and the United States: Effects of the 2008–09 financial crisis," Journal of Asian Economics, Elsevier, vol. 23(4), pages 344-352.
    28. Cevik, Nuket Kirci & Cevik, Emrah I. & Dibooglu, Sel, 2020. "Oil prices, stock market returns and volatility spillovers: Evidence from Turkey," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 597-614.
    29. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Modelling the volatility transmission and conditional correlations between A and B shares in forecasting value-at-risk," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 155-171.
    30. González-Sánchez, Mariano, 2018. "Causality in the EMU sovereign bond markets," Finance Research Letters, Elsevier, vol. 26(C), pages 281-290.
    31. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    32. Pantelidis, Theologos & Pittis, Nikitas, 2004. "Testing for Granger causality in variance in the presence of causality in mean," Economics Letters, Elsevier, vol. 85(2), pages 201-207, November.
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    161. Matthieu Droumaguet & Tomasz Wozniak, 2012. "Bayesian Testing of Granger Causality in Markov-Switching VARs," Economics Working Papers ECO2012/06, European University Institute.
    162. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
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    175. Saafi Sami & Farhat Abdeljelil & Haj Mohamed Meriem Bel, 2015. "Testing the relationships between shadow economy and unemployment: empirical evidence from linear and nonlinear tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 585-608, December.
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    183. Alper Gormus & Ugur Soytas, 2023. "Financial Sector Troubles and Energy Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 357-363, March.
    184. Rangan Gupta & Patrick Kanda & Aviral Kumar Tiwari & Mark E. Wohar, 2018. "Time-Varying Predictability of Oil Market Movements Over a Century of Data: The Role of US Financial Stress," Working Papers 201848, University of Pretoria, Department of Economics.
    185. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    186. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.
    187. Baklaci, Hasan Fehmi & Aydoğan, Berna & Yelkenci, Tezer, 2020. "Impact of stock market trading on currency market volatility spillovers," Research in International Business and Finance, Elsevier, vol. 52(C).
    188. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
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    194. Cevik, Emrah Ismail & Gunay, Samet & Dibooglu, Sel & Yıldırım, Durmuş Çağrı, 2023. "The impact of expected and unexpected events on Bitcoin price development: Introduction of futures market and COVID-19," Finance Research Letters, Elsevier, vol. 54(C).
    195. Ngo Thai Hung, 2020. "Market integration among foreign exchange rate movements in central and eastern European countries," Society and Economy, Akadémiai Kiadó, Hungary, vol. 42(1), pages 1-20, March.
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    199. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
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    203. Bajo-Rubio, Oscar & Berke, Burcu & McMillan, David, 2017. "The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises," Research in International Business and Finance, Elsevier, vol. 41(C), pages 577-589.
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    205. Gormus, Alper & Nazlioglu, Saban & Soytas, Ugur, 2018. "High-yield bond and energy markets," Energy Economics, Elsevier, vol. 69(C), pages 101-110.
    206. Liu, Xiangli & Cheng, Siwei & Wang, Shouyang & Hong, Yongmiao & Li, Yi, 2008. "An empirical study on information spillover effects between the Chinese copper futures market and spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 899-914.
    207. Gormus, N. Alper & Atinc, Guclu, 2016. "Volatile oil and the U.S. economy," Economic Analysis and Policy, Elsevier, vol. 50(C), pages 62-73.
    208. Hassan, M. Kabir & Kayhana, Selim & Bayatb, Tayfur, 2016. "The Relation between Return and Volatility in ETFs Traded in Borsa Istanbul: Is there any Difference between Islamic and Conventional ETFs?," Islamic Economic Studies, The Islamic Research and Training Institute (IRTI), vol. 24, pages 45-76.
    209. Kumar, Satish, 2018. "Price discovery in emerging currency markets," Research in International Business and Finance, Elsevier, vol. 46(C), pages 528-536.
    210. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.
    211. Korkmaz, Turhan & Çevik, Emrah İ. & Atukeren, Erdal, 2012. "Return and volatility spillovers among CIVETS stock markets," Emerging Markets Review, Elsevier, vol. 13(2), pages 230-252.
    212. Ginny ju-ann Yang & Koyin Chang & Yung-Hsiang Ying & Chen-hsun Lee, 2014. "Spillover Effects of Chinese Stock Markets," Economics Bulletin, AccessEcon, vol. 34(1), pages 200-205.
    213. Yuki Toyoshima, 2018. "Testing for Causality-In-Mean and Variance between the UK Housing and Stock Markets," JRFM, MDPI, vol. 11(2), pages 1-10, April.
    214. Caston Sigauke & Rosinah Mukhodobwane & Wilbert Chagwiza & Winston Garira, 2022. "Asymptotic Dependence Modelling of the BRICS Stock Markets," IJFS, MDPI, vol. 10(3), pages 1-32, July.
    215. Wee-Yeap Lau & You-How Go, 2018. "Dynamic Causality Between Stock Return and Exchange Rate: Is Stock-Oriented Hypothesis More Relevant in Malaysia?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(2), pages 137-157, June.

  49. Yongmiao Hong, 2000. "Generalized spectral tests for serial dependence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(3), pages 557-574.

    Cited by:

    1. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.
    3. Escanciano, Juan Carlos & Velasco, Carlos, 2003. "Generalized spectral tests for the martingale difference hypothesis," DES - Working Papers. Statistics and Econometrics. WS ws035312, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Zaichao Du, 2009. "Nonparametric Bootstrap Tests for Independence of Generalized Errors," CAEPR Working Papers 2009-023, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    5. Holger Dette & Marc Hallin & Tobias Kley & Stanislav Volgushev, 2011. "Of Copulas, Quantiles, Ranks and Spectra - An L1-Approach to Spectral Analysis," Working Papers ECARES ECARES 2011-038, ULB -- Universite Libre de Bruxelles.
    6. Stefan Birr & Stanislav Volgushev & Tobias Kley & Holger Dette & Marc Hallin, 2015. "Quantile Spectral Analysis for Locally Stationary Time Series," Working Papers ECARES ECARES 2015-27, ULB -- Universite Libre de Bruxelles.
    7. Ta‐Hsin Li, 2021. "Quantile‐frequency analysis and spectral measures for diagnostic checks of time series with nonlinear dynamics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 270-290, March.
    8. Gao, Jiti & Pan, Guangming & Yang, Yanrong, 2012. "Testing Independence for a Large Number of High–Dimensional Random Vectors," MPRA Paper 45073, University Library of Munich, Germany, revised 15 Mar 2013.
    9. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    10. Aviral Kumar Tiwari & Muhammad Shahbaz & Rabeh Khalfaoui & Rizwan Ahmed & Shawkat Hammoudeh, 2024. "Directional predictability from energy markets to exchange rates and stock markets in the emerging market countries (E7 + 1): New evidence from cross‐quantilogram approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 719-789, January.
    11. Degui Li & Oliver Linton & Zudi Lu, 2010. "Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate," STICERD - Econometrics Paper Series 549, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    12. Nasri, Bouchra R., 2022. "Tests of serial dependence for multivariate time series with arbitrary distributions," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    13. Zaichao Du & Juan Carlos Escanciano, 2015. "A Nonparametric Distribution-Free Test for Serial Independence of Errors," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1011-1034, December.
    14. Li, Degui & Lu, Zudi & Linton, Oliver, 2012. "Local Linear Fitting Under Near Epoch Dependence: Uniform Consistency With Convergence Rates," Econometric Theory, Cambridge University Press, vol. 28(5), pages 935-958, October.
    15. Shibin Zhang, 2023. "A copula spectral test for pairwise time reversibility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(5), pages 705-729, October.
    16. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Testing Serial Independence via Density-Based Measures of Divergence," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 627-641, September.
    17. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    18. Yuichi Goto & Tobias Kley & Ria Van Hecke & Stanislav Volgushev & Holger Dette & Marc Hallin, 2021. "The Integrated Copula Spectrum," Working Papers ECARES 2021-29, ULB -- Universite Libre de Bruxelles.
    19. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    20. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers 29/14, Institute for Fiscal Studies.
    21. Lanh Tran & Ba Chu & Chunfeng Huang & Kim P. Huynh, 2014. "Adaptive permutation tests for serial independence," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 183-208, August.
    22. Zhang, Shibin, 2019. "Bayesian copula spectral analysis for stationary time series," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 166-179.
    23. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into Multivariate Variance Ratio Statistics and their application to Stock Market Predictability," Cambridge Working Papers in Economics 1552, Faculty of Economics, University of Cambridge.
    24. Ghoudi, Kilani & Kulperger, Reg J. & Rémillard, Bruno, 2001. "A Nonparametric Test of Serial Independence for Time Series and Residuals," Journal of Multivariate Analysis, Elsevier, vol. 79(2), pages 191-218, November.
    25. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers CWP29/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    27. Ta-Hsin Li, 2019. "Quantile-Frequency Analysis and Spectral Divergence Metrics for Diagnostic Checks of Time Series With Nonlinear Dynamics," Papers 1908.02545, arXiv.org.
    28. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into multivariate variance ratio statistics and their application to stock market predictability," CeMMAP working papers 13/15, Institute for Fiscal Studies.

  50. Hong, Yongmiao & Shehadeh, Ramsey D, 1999. "A New Test for ARCH Effects and Its Finite-Sample Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 91-108, January.

    Cited by:

    1. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    2. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
    3. Robin L. Lumsdaine & Serena Ng, 1998. "Testing for ARCH in the Presence of a Possibly Misspecified Conditional Mean," Boston College Working Papers in Economics 370, Boston College Department of Economics.
    4. Yoon-Jin Lee & Yongmiao Hong, 2004. "Specification Testing for Multivariate Time Series Volatility Models," Econometric Society 2004 Far Eastern Meetings 696, Econometric Society.
    5. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    6. Gabriele Fiorentini & Enrique Sentana, 2019. "New testing approaches for mean-variance predictability," Working Paper series 19-01, Rimini Centre for Economic Analysis.
    7. Duchesne, Pierre, 2004. "On robust testing for conditional heteroscedasticity in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 227-256, June.
    8. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
    9. Par Sjolander, 2010. "A stationary unbiased finite sample ARCH-LM test procedure," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 1019-1033.
    10. Seonjin Kim, 2015. "Hypothesis Testing For Arch Models: A Multiple Quantile Regressions Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 26-38, January.
    11. Y. K. Tse, 2002. "Residual-based diagnostics for conditional heteroscedasticity models," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 358-374, June.
    12. Tsvetomir Tsvetkov & Sonya Georgieva, 2022. "Inflation, Inflation Instability and Nominal Uncertainty in Bulgarian Economy," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 41-64.
    13. Jin Lee, 2000. "One-Sided Testing for ARCH Effect Using Wavelets," Econometric Society World Congress 2000 Contributed Papers 1214, Econometric Society.

  51. Yongmiao Hong, 1998. "Testing for pairwise serial independence via the empirical distribution function," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 429-453.

    Cited by:

    1. Juan Mora & Miguel A. Delgado, 1999. "- A Nonparametric Test For Serial Independence Of Regression Errors," Working Papers. Serie AD 1999-28, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. Delgado, Miguel A. & Mora, Juan, 1998. "A nonparametric test for serial independence of errors in linear regression," DES - Working Papers. Statistics and Econometrics. WS 4675, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Meintanis, Simos G. & Iliopoulos, George, 2008. "Fourier methods for testing multivariate independence," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1884-1895, January.
    4. Diks Cees & Manzan Sebastiano, 2002. "Tests for Serial Independence and Linearity Based on Correlation Integrals," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    5. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    6. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, Center for Economic and Financial Research (CEFIR).
    7. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
    8. Cai, Zongwu & Hong, Yongmiao, 2003. "Nonparametric Methods in Continuous-Time Finance: A Selective Review," SFB 373 Discussion Papers 2003,15, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Christian Genest & Bruno Rémillard, 2004. "Test of independence and randomness based on the empirical copula process," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(2), pages 335-369, December.
    10. Lanh Tran & Ba Chu & Chunfeng Huang & Kim P. Huynh, 2014. "Adaptive permutation tests for serial independence," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 183-208, August.
    11. Ghoudi, Kilani & Kulperger, Reg J. & Rémillard, Bruno, 2001. "A Nonparametric Test of Serial Independence for Time Series and Residuals," Journal of Multivariate Analysis, Elsevier, vol. 79(2), pages 191-218, November.
    12. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
    13. Cees Diks & Sebastiano Manzan, 2001. "Tests for Serial Independence and Linearity based on Correlation Integrals," Tinbergen Institute Discussion Papers 01-085/1, Tinbergen Institute.

  52. Yongmiao Hong, 1997. "One‐sided testing for conditional heteroskedasticity in time series models," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(3), pages 253-277, May.

    Cited by:

    1. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.

  53. Hong, Yongmiao, 1996. "Consistent Testing for Serial Correlation of Unknown Form," Econometrica, Econometric Society, vol. 64(4), pages 837-864, July.

    Cited by:

    1. Duchesne, Pierre & Roy, Roch, 2004. "On consistent testing for serial correlation of unknown form in vector time series models," Journal of Multivariate Analysis, Elsevier, vol. 89(1), pages 148-180, April.
    2. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    3. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    4. Li, Muyi & Zhang, Yanfen, 2022. "Bootstrapping multivariate portmanteau tests for vector autoregressive models with weak assumptions on errors," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
    5. Ian Dew-Becker & Rhys Bidder, 2015. "Long-Run Risk is the Worst-Case Scenario," 2015 Meeting Papers 490, Society for Economic Dynamics.
    6. Yang, Xiye, 2020. "Time-invariant restrictions of volatility functionals: Efficient estimation and specification tests," Journal of Econometrics, Elsevier, vol. 215(2), pages 486-516.
    7. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    8. Hidalgo, Javier, 2009. "Goodness of fit for lattice processes," Journal of Econometrics, Elsevier, vol. 151(2), pages 113-128, August.
    9. Jia Li & Peter C. B. Phillips & Shuping Shi & Jun Yu, 2022. "Weak Identification of Long Memory with Implications for Inference," Cowles Foundation Discussion Papers 2334, Cowles Foundation for Research in Economics, Yale University.
    10. Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
    11. Hwang, Min & Quigley, John M., 2010. "Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns," Berkeley Program on Housing and Urban Policy, Working Paper Series qt41k6c76w, Berkeley Program on Housing and Urban Policy.
    12. Amélie Charles & Olivier Darné & Jae H. Kim, 2010. "Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence from Major Foreign Exchange Rates," Working Papers hal-00547722, HAL.
    13. Hong, Yongmiao, 1996. "Testing for independence between two covariance stationary time series," MPRA Paper 108731, University Library of Munich, Germany.
    14. Li, Linyuan & Yao, Shan & Duchesne, Pierre, 2014. "On wavelet-based testing for serial correlation of unknown form using Fan’s adaptive Neyman method," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 308-327.
    15. Zhu, Ke, 2015. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," MPRA Paper 61930, University Library of Munich, Germany.
    16. William A. Barnett & Melvin J. Hinich & Piyu Yue, 2000. "The Exact Theoretical Rational Expectations Monetary Aggregate," Macroeconomics 0003004, University Library of Munich, Germany.
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Chapters

  1. Ai Han & Yongmiao Hong & Shouyang Wang & Xin Yun, 2016. "A Vector Autoregressive Moving Average Model for Interval-Valued Time Series Data," Advances in Econometrics, in: Essays in Honor of Aman Ullah, volume 36, pages 417-460, Emerald Group Publishing Limited.

    Cited by:

    1. Samadi, S. Yaser & Billard, Lynne, 2021. "Analysis of dependent data aggregated into intervals," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    2. Babel Raïssa Guemdjo Kamdem & Jules Sadefo-Kamdem & Carlos Ougouyandjou, 2020. "On Random Extended Intervals and their ARMA Processes," Working Papers hal-03169516, HAL.
    3. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
    4. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
    5. Sun, Yuying & Zhang, Xun & Hong, Yongmiao & Wang, Shouyang, 2019. "Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling," Energy Economics, Elsevier, vol. 78(C), pages 165-173.
    6. Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
    7. Qing Liu & Huina Jin & Xiang Bai & Jinliang Zhang, 2023. "Prediction and Analysis of the Price of Carbon Emission Rights in Shanghai: Under the Background of COVID-19 and the Russia–Ukraine Conflict," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    8. Babel Raïssa Guemdjo Kamdem & Jules Sadefo-Kamdem & Carlos Ogouyandjou, 2021. "An Abelian Group way to study Random Extended Intervals and their ARMA Processes," Working Papers hal-03174631, HAL.

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