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Yong Li Sr.

Personal Details

First Name:Yong
Middle Name:
Last Name:Li
Suffix:Sr.
RePEc Short-ID:pli624

Affiliation

Hanqing Advanced Institute of Economics and Finance
Renmin University of China

Beijing, China
http://www.hanqing.ruc.edu.cn/




RePEc:edi:haruccn (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Chang, C-L. & Li, Y. & McAleer, M.J., 2015. "Volatility Spillovers Between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Econometric Institute Research Papers EI2015-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Chong, Terence Tai Leung & Ding, Yue & Li, Yong, 2015. "Executive Stock Option Pricing in China under Stochastic Volatility," MPRA Paper 63397, University Library of Munich, Germany.
  3. Tao Zeng & Yong Li & Jun Yu, 2014. "Deviance Information Criterion for Comparing VAR Models," Working Papers 01-2014, Singapore Management University, School of Economics.
  4. Yong Li & Xiao-Bin Liu & Jun Yu, 2014. "A Bayesian Chi-Squared Test for Hypothesis Testing," Working Papers 03-2014, Singapore Management University, School of Economics.
  5. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
  6. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
  7. Yong Li & Jun Yu, 2010. "A New Bayesian Unit Root Test in Stochastic Volatility Models," Working Papers 21-2010, Singapore Management University, School of Economics, revised Oct 2010.

    repec:skb:wpaper:cofie-04-2012 is not listed on IDEAS

Articles

  1. Cao, Yijia & Wang, Xifan & Li, Yong & Tan, Yi & Xing, Jianbo & Fan, Ruixiang, 2016. "A comprehensive study on low-carbon impact of distributed generations on regional power grids: A case of Jiangxi provincial power grid in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 766-778.
  2. Li, Yong & Yang, Jie & Song, Jian, 2016. "Nano-energy system coupling model and failure characterization of lithium ion battery electrode in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1250-1261.
  3. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
  4. Xing, Jiamin & Li, Yong, 2016. "Nonlinear Lyapunov criteria for stochastic explosive solutions," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 63-67.
  5. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
  6. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
  7. Li, Yong & Yang, Jie & Song, Jian, 2015. "Electromagnetic effects model and design of energy systems for lithium batteries with gradient structure in sustainable energy electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 842-851.
  8. Ye, Qing & Yang, Xiaoguang & Dai, Shuwei & Chen, Guangsheng & Li, Yong & Zhang, Caixia, 2015. "Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China," Agricultural Water Management, Elsevier, vol. 159(C), pages 35-44.
  9. Li, Yong & Yang, Jie & Song, Jian, 2015. "Microscale characterization of coupled degradation mechanism of graded materials in lithium batteries of electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1445-1461.
  10. Terence Tai Leung Chong & Yue Ding & Yong Li, 2015. "Executive Stock Option Pricing in China Under Stochastic Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(10), pages 953-960, October.
  11. Li, Yong & Zeng, Tao & Yu, Jun, 2014. "A new approach to Bayesian hypothesis testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 602-612.
  12. Li Yong & Jie Zhang, 2014. "Bayesian testing for jumps in stochastic volatility models with correlated jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1693-1700, October.
  13. Li, Yong & Huang, Wei-Ping & Zhang, Jie, 2013. "Forecasting volatility in the Chinese stock market under model uncertainty," Economic Modelling, Elsevier, vol. 35(C), pages 231-234.
  14. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.
  15. Jin-Yu Zhang & Yong Li & Zhu-Ming Chen, 2013. "Unit Root Hypothesis in the Presence of Stochastic Volatility, a Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 89-100, January.
  16. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
  17. Li, Yong & Chong, Terence Tai-Leung & Zhang, Jie, 2012. "Testing for a unit root in the presence of stochastic volatility and leverage effect," Economic Modelling, Elsevier, vol. 29(5), pages 2035-2038.
  18. Li, Yong & Yu, Jun, 2012. "Bayesian hypothesis testing in latent variable models," Journal of Econometrics, Elsevier, vol. 166(2), pages 237-246.
  19. Jin-Guan Lin & Ji Chen & Yong Li, 2012. "Bayesian Analysis of Student t Linear Regression with Unknown Change-Point and Application to Stock Data Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 203-217, October.
  20. Yong Li & Zhongxin Ni & Jie Zhang, 2011. "An Efficient Stochastic Simulation Algorithm for Bayesian Unit Root Testing in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 237-248, March.
  21. Jin-Guan Lin & Li-Xing Zhu & Chun-Zheng Cao & Yong Li, 2011. "Tests of heteroscedasticity and correlation in multivariate t regression models with AR and ARMA errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1509-1531, August.

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. Chang, C-L. & Li, Y. & McAleer, M.J., 2015. "Volatility Spillovers Between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Econometric Institute Research Papers EI2015-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    2. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures," Working Papers 201925, University of Pretoria, Department of Economics.
    3. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "How are VIX and Stock Index ETF Related?," Documentos de Trabajo del ICAE 2016-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    4. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
    5. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2018. "Latent Volatility Granger Causality and Spillovers in Renewable Energy and Crude Oil ETFs," Tinbergen Institute Discussion Papers 18-052/III, Tinbergen Institute.
    6. David E. Allen & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2015. "Multivariate Volatility Impulse Response Analysis of GFC News Events," Documentos de Trabajo del ICAE 2015-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2017. "Volatility spillover and multivariate volatility impulse response analysis of GFC news events," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3246-3262, July.
    8. Chia-Lin Chang & Michael McAleer & Chien-Hsun Wang, 2017. "An Econometric Analysis of ETF and ETF Futures in Financial and Energy Markets Using Generated Regressors," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 6(1), pages 1-24, December.
    9. Chia-Lin Chang & Michael McAleer & Te-Ke Mai, 2018. "Establishing National Carbon Emission Prices for China," Documentos de Trabajo del ICAE 2018-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    10. Chang, C-L. & McAleer, M.J. & Wang, Y., 2016. "Testing Co-Volatility Spillovers for Natural Gas Spot, Futures and ETF Spot using Dynamic Conditional Covariances," Econometric Institute Research Papers EI2016-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. David E. Allen & Chialin Chang & Michael McAleer & Abhay K Singh, 2018. "A cointegration analysis of agricultural, energy and bio-fuel spot, and futures prices," Applied Economics, Taylor & Francis Journals, vol. 50(7), pages 804-823, February.
    12. Gaoke Liao & Zhenghui Li & Ziqing Du & Yue Liu, 2019. "The Heterogeneous Interconnections between Supply or Demand Side and Oil Risks," Energies, MDPI, Open Access Journal, vol. 12(11), pages 1-17, June.
    13. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "Risk Spillovers in Returns for Chinese and International Tourists to Taiwan," Tinbergen Institute Discussion Papers 18-031/III, Tinbergen Institute.
    14. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility spillovers and causality of carbon emissions, oil and coal spot and futures for the EU and USA," Documentos de Trabajo del ICAE 2017-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    15. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, Open Access Journal, vol. 12(8), pages 1-24, April.
    16. Duc Hong Vo & Tan Ngoc Vu & Anh The Vo & Michael McAleer, 2019. "Modelling the relationship between crude oil and agricultural commodity prices," Documentos de Trabajo del ICAE 2019-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    17. Michael McAleer, 2015. "The Fundamental Equation in Tourism Finance," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 8(4), pages 1-6, December.
    18. Chang, C-L. & Hsieh, T-L. & McAleer, M.J., 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," Econometric Institute Research Papers EI2018-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures related for Intra-Day Data?," Tinbergen Institute Discussion Papers 16-006/III, Tinbergen Institute.
    20. Chang, C-L. & Liu, C-P. & McAleer, M.J., 2016. "Volatility Spillovers for Spot, Futures, and ETF Prices in Energy and Agriculture," Econometric Institute Research Papers EI2016-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    21. Zhicheng Liang & Junwei Wang & Kin Keung Lai, 2020. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 169-193, February.
    22. Matteo Bonato & Rangan Gupta & Chi Keung Marco Lau & Shixuan Wang, 2019. "Moments-Based Spillovers across Gold and Oil Markets," Working Papers 201966, University of Pretoria, Department of Economics.

  2. Chong, Terence Tai Leung & Ding, Yue & Li, Yong, 2015. "Executive Stock Option Pricing in China under Stochastic Volatility," MPRA Paper 63397, University Library of Munich, Germany.

    Cited by:

    1. Zhiwei Su & Xingchun Wang, 2019. "Pricing executive stock options with averaging features under the Heston–Nandi GARCH model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(9), pages 1056-1084, September.
    2. Wang, Xingchun, 2018. "Valuing executive stock options under correlated employment shocks," Finance Research Letters, Elsevier, vol. 27(C), pages 38-45.

  3. Yong Li & Xiao-Bin Liu & Jun Yu, 2014. "A Bayesian Chi-Squared Test for Hypothesis Testing," Working Papers 03-2014, Singapore Management University, School of Economics.

    Cited by:

    1. Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
    2. Antonio Parisi & B. Liseo, 2018. "Objective Bayesian analysis for the multivariate skew-t model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 277-295, June.
    3. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Specification tests based on MCMC output," Journal of Econometrics, Elsevier, vol. 207(1), pages 237-260.
    4. Li, Yong & Liu, Xiaobin & Zeng, Tao & Yu, Jun, 2018. "A Posterior-Based Wald-Type Statistic for Hypothesis Testing," Economics and Statistics Working Papers 8-2018, Singapore Management University, School of Economics.
    5. Yong Li & Jun Yu, 2019. "An Improved Bayesian Unit Root Test in Stochastic Volatility Models," Annals of Economics and Finance, Society for AEF, vol. 20(1), pages 103-122, May.
    6. Zhang, Yonghui & Chen, Zhongtian & Li, Yong, 2017. "Bayesian testing for short term interest rate models," Finance Research Letters, Elsevier, vol. 20(C), pages 146-152.
    7. Chen, Shyh-Wei & Hsu, Chi-Sheng & Xie, Zixong, 2016. "Are there periodically collapsing bubbles in the stock markets? New international evidence," Economic Modelling, Elsevier, vol. 52(PB), pages 442-451.
    8. Jin-Yu Zhang & Zhong-Tian Chen & Yong Li, 2019. "Bayesian Testing for Leverage Effect in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1153-1164, March.
    9. Guanhao Feng & Jingyu He, 2019. "Factor Investing: A Bayesian Hierarchical Approach," Papers 1902.01015, arXiv.org, revised Sep 2020.

  4. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.

    Cited by:

    1. Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Wiper, Michael Peter & Galán Camacho, Jorge Eduardo & Lopes Moreira Da Veiga, María Helena, 2013. "Bayesian analysis of dynamic effects in inefficiency : evidence from the Colombian banking sector," DES - Working Papers. Statistics and Econometrics. WS ws131918, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Jorge E. Galán & Michael G. Pollitt, 2014. "Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities," Working Papers EPRG 1403, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    4. Galán, Jorge E. & Sarmiento, Miguel, 2014. "Heterogeneous effects of risk-taking on bank efficiency : a stochastic frontier model with random coefficients," DES - Working Papers. Statistics and Econometrics. WS ws142013, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    6. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    7. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    8. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.
    10. Veiga, Helena & Ramos, Sofía B. & Galán, Jorge, 2015. "An analysis of the dynamics of efficiency of mutual funds," DES - Working Papers. Statistics and Econometrics. WS ws1517, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Vo, Minh & Cohen, Michael & Boulter, Terry, 2015. "Asymmetric risk and return: Evidence from the Australian Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 558-573.

  5. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.

    Cited by:

    1. Kensuke Okada & Shin-ichi Mayekawa, 2018. "Post-processing of Markov chain Monte Carlo output in Bayesian latent variable models with application to multidimensional scaling," Computational Statistics, Springer, vol. 33(3), pages 1457-1473, September.
    2. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    3. Tao Zeng & Yong Li & Jun Yu, 2014. "Deviance Information Criterion for Comparing VAR Models," Advances in Econometrics, in: Yoosoon Chang & Thomas B. Fomby & Joon Y. Park (ed.),Essays in Honor of Peter C. B. Phillips, volume 33, pages 615-637, Emerald Publishing Ltd.
    4. Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
    5. Li, Yong & Liu, Xiaobin & Zeng, Tao & Yu, Jun, 2018. "A Posterior-Based Wald-Type Statistic for Hypothesis Testing," Economics and Statistics Working Papers 8-2018, Singapore Management University, School of Economics.
    6. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    7. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    8. Jin-Yu Zhang & Yong Li & Zhu-Ming Chen, 2013. "Unit Root Hypothesis in the Presence of Stochastic Volatility, a Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 89-100, January.
    9. Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.
    10. Zhao, Yan-Yong & Lin, Jin-Guan & Xu, Pei-Rong & Ye, Xu-Guo, 2015. "Orthogonality-projection-based estimation for semi-varying coefficient models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 204-221.
    11. Li, Yong & Zeng, Tao & Yu, Jun, 2014. "A new approach to Bayesian hypothesis testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 602-612.
    12. Yong Li & Jun Yu, 2019. "An Improved Bayesian Unit Root Test in Stochastic Volatility Models," Annals of Economics and Finance, Society for AEF, vol. 20(1), pages 103-122, May.
    13. Zhang, Yonghui & Chen, Zhongtian & Li, Yong, 2017. "Bayesian testing for short term interest rate models," Finance Research Letters, Elsevier, vol. 20(C), pages 146-152.
    14. Yijie Peng & Michael C. Fu & Jian-Qiang Hu, 2016. "Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1393-1411, September.
    15. Tian, Yuzhu & Zhu, Qianqian & Tian, Maozai, 2016. "Estimation of linear composite quantile regression using EM algorithm," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 183-191.
    16. Chen, Shyh-Wei & Hsu, Chi-Sheng & Xie, Zixong, 2016. "Are there periodically collapsing bubbles in the stock markets? New international evidence," Economic Modelling, Elsevier, vol. 52(PB), pages 442-451.
    17. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
    18. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.
    19. Li, Yong & Chong, Terence Tai-Leung & Zhang, Jie, 2012. "Testing for a unit root in the presence of stochastic volatility and leverage effect," Economic Modelling, Elsevier, vol. 29(5), pages 2035-2038.
    20. Zhang, Duo & Wang, Min, 2018. "Objective Bayesian inference for the intraclass correlation coefficient in linear models," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 292-296.
    21. Jin-Yu Zhang & Zhong-Tian Chen & Yong Li, 2019. "Bayesian Testing for Leverage Effect in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1153-1164, March.

  6. Yong Li & Jun Yu, 2010. "A New Bayesian Unit Root Test in Stochastic Volatility Models," Working Papers 21-2010, Singapore Management University, School of Economics, revised Oct 2010.

    Cited by:

    1. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    2. Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.

Articles

  1. Cao, Yijia & Wang, Xifan & Li, Yong & Tan, Yi & Xing, Jianbo & Fan, Ruixiang, 2016. "A comprehensive study on low-carbon impact of distributed generations on regional power grids: A case of Jiangxi provincial power grid in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 766-778.

    Cited by:

    1. Wang, Junfeng & He, Shutong & Qiu, Ye & Liu, Nan & Li, Yongjian & Dong, Zhanfeng, 2018. "Investigating driving forces of aggregate carbon intensity of electricity generation in China," Energy Policy, Elsevier, vol. 113(C), pages 249-257.
    2. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    3. Prakash, Prem & Khatod, Dheeraj K., 2016. "Optimal sizing and siting techniques for distributed generation in distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 111-130.
    4. Guerrero-Rodríguez, N.F. & Rey-Boué, Alexis B. & Bueno, E.J. & Ortiz, Octavio & Reyes-Archundia, Enrique, 2017. "Synchronization algorithms for grid-connected renewable systems: Overview, tests and comparative analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 629-643.
    5. Burmester, Daniel & Rayudu, Ramesh & Seah, Winston & Akinyele, Daniel, 2017. "A review of nanogrid topologies and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 760-775.
    6. Qingyou Yan & Yaxian Wang & Tomas Baležentis & Yikai Sun & Dalia Streimikiene, 2018. "Energy-Related CO 2 Emission in China’s Provincial Thermal Electricity Generation: Driving Factors and Possibilities for Abatement," Energies, MDPI, Open Access Journal, vol. 11(5), pages 1-25, April.
    7. Tian-tian Feng & Yi-sheng Yang & Yu-heng Yang & Dan-dan Wang, 2017. "Application Status and Problem Investigation of Distributed Generation in China: The Case of Natural Gas, Solar and Wind Resources," Sustainability, MDPI, Open Access Journal, vol. 9(6), pages 1-19, June.
    8. Yi, Bo-Wen & Xu, Jin-Hua & Fan, Ying, 2016. "Inter-regional power grid planning up to 2030 in China considering renewable energy development and regional pollutant control: A multi-region bottom-up optimization model," Applied Energy, Elsevier, vol. 184(C), pages 641-658.

  2. Li, Yong & Yang, Jie & Song, Jian, 2016. "Nano-energy system coupling model and failure characterization of lithium ion battery electrode in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1250-1261.

    Cited by:

    1. Li, Yong & Yang, Jie & Song, Jian, 2017. "Efficient storage mechanisms and heterogeneous structures for building better next-generation lithium rechargeable batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1503-1512.
    2. Li, Yong & Yang, Jie & Song, Jian, 2017. "Structure models and nano energy system design for proton exchange membrane fuel cells in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 160-172.
    3. Li, Yong & Yang, Jie & Song, Jian, 2016. "Structural model, size effect and nano-energy system design for more sustainable energy of solid state automotive battery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 685-697.
    4. Li, Yong & Yang, Jie & Song, Jian, 2017. "Design structure model and renewable energy technology for rechargeable battery towards greener and more sustainable electric vehicle," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 19-25.

  3. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.

    Cited by:

    1. Chen, Jianrui & Wang, Hua & Wang, Lina & Liu, Weiwei, 2016. "A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 482-492.
    2. Chen, Jianrui & Wei, Lidan & Uliji, & Zhang, Li, 2018. "Dynamic evolutionary clustering approach based on time weight and latent attributes for collaborative filtering recommendation," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 8-18.
    3. Ma, Yinghong & Zhu, Xiaoyu & Yu, Qinglin, 2019. "Clusters detection based leading eigenvector in signed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1263-1275.
    4. Zhu, Xiaoyu & Ma, Yinghong & Liu, Zhiyuan, 2018. "A novel evolutionary algorithm on communities detection in signed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 938-946.

  4. Xing, Jiamin & Li, Yong, 2016. "Nonlinear Lyapunov criteria for stochastic explosive solutions," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 63-67.

    Cited by:

    1. Dan Pirjol & Lingjiong Zhu, 2019. "Explosion in the quasi-Gaussian HJM model," Papers 1908.07102, arXiv.org.
    2. Dan Pirjol & Lingjiong Zhu, 2018. "Explosion in the quasi-Gaussian HJM model," Finance and Stochastics, Springer, vol. 22(3), pages 643-666, July.

  5. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    See citations under working paper version above.
  6. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.

    Cited by:

    1. Huang, Jianbai & Tang, Jing & Zhang, Hongwei, 2020. "The effect of investors’ information search behaviors on rebar market return dynamics using high frequency data," Resources Policy, Elsevier, vol. 66(C).
    2. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    3. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
    4. Liu, Chang & Hu, Zhenhua & Li, Yan & Liu, Shaojun, 2017. "Forecasting copper prices by decision tree learning," Resources Policy, Elsevier, vol. 52(C), pages 427-434.
    5. Wang, Chao & Zhang, Xinyi & Wang, Minggang & Lim, Ming K. & Ghadimi, Pezhman, 2019. "Predictive analytics of the copper spot price by utilizing complex network and artificial neural network techniques," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    6. Wang, Xinya & Liu, Huifang & Huang, Shupei, 2019. "Identification of the daily seasonality in gold returns and volatilities: Evidence from Shanghai and London," Resources Policy, Elsevier, vol. 61(C), pages 522-531.
    7. Yongmei Fang & Bo Guan & Shangjuan Wu & Saeed Heravi, 2020. "Optimal forecast combination based on ensemble empirical mode decomposition for agricultural commodity futures prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 877-886, September.
    8. Dehghani, Hesam & Bogdanovic, Dejan, 2018. "Copper price estimation using bat algorithm," Resources Policy, Elsevier, vol. 55(C), pages 55-61.
    9. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    10. Dong, Di & An, Haizhong & Huang, Shupei, 2017. "The transfer of embodied carbon in copper international trade: An industry chain perspective," Resources Policy, Elsevier, vol. 52(C), pages 173-180.

  7. Li, Yong & Yang, Jie & Song, Jian, 2015. "Electromagnetic effects model and design of energy systems for lithium batteries with gradient structure in sustainable energy electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 842-851.

    Cited by:

    1. Ummartyotin, S. & Bunnak, N. & Manuspiya, H., 2016. "A comprehensive review on modified clay based composite for energy based materials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 466-472.
    2. Li, Yong & Yang, Jie & Song, Jian, 2017. "Efficient storage mechanisms and heterogeneous structures for building better next-generation lithium rechargeable batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1503-1512.
    3. Li, Yong & Yang, Jie & Song, Jian, 2017. "Structure models and nano energy system design for proton exchange membrane fuel cells in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 160-172.
    4. Mihai Machedon-Pisu & Paul Nicolae Borza, 2019. "Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study," Sustainability, MDPI, Open Access Journal, vol. 12(1), pages 1-24, December.
    5. Li, Yong & Yang, Jie & Song, Jian, 2016. "Structural model, size effect and nano-energy system design for more sustainable energy of solid state automotive battery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 685-697.
    6. Li, Yong & Yang, Jie & Song, Jian, 2016. "Nano-energy system coupling model and failure characterization of lithium ion battery electrode in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1250-1261.
    7. Li, Yong & Yang, Jie & Song, Jian, 2017. "Design principles and energy system scale analysis technologies of new lithium-ion and aluminum-ion batteries for sustainable energy electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 645-651.
    8. Li, Yong & Yang, Jie & Song, Jian, 2017. "Design structure model and renewable energy technology for rechargeable battery towards greener and more sustainable electric vehicle," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 19-25.
    9. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.

  8. Ye, Qing & Yang, Xiaoguang & Dai, Shuwei & Chen, Guangsheng & Li, Yong & Zhang, Caixia, 2015. "Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China," Agricultural Water Management, Elsevier, vol. 159(C), pages 35-44.

    Cited by:

    1. Li Jiang & Xin Chen & Fei Lun & Zhihua Pan & Jiaheng Niu & Chenyang Ding & Lijun Meng & Guoliang Zhang & Charles Peter Mgeni & Stefan Sieber & Pingli An, 2019. "Spatial Distribution and Changes of the Realizable Triple Cropping System in China," Sustainability, MDPI, Open Access Journal, vol. 11(6), pages 1-18, March.
    2. Ding, Yimin & Wang, Weiguang & Song, Ruiming & Shao, Quanxi & Jiao, Xiyun & Xing, Wanqiu, 2017. "Modeling spatial and temporal variability of the impact of climate change on rice irrigation water requirements in the middle and lower reaches of the Yangtze River, China," Agricultural Water Management, Elsevier, vol. 193(C), pages 89-101.
    3. Wang, Jianqing & Liu, Xiaoyu & Cheng, Kun & Zhang, Xuhui & Li, Lianqing & Pan, Genxing, 2018. "Winter wheat water requirement and utilization efficiency under simulated climate change conditions: A Penman-Monteith model evaluation," Agricultural Water Management, Elsevier, vol. 197(C), pages 100-109.
    4. F. Castro-Llanos & G. Hyman & J. Rubiano & J. Ramirez-Villegas & H. Achicanoy, 2019. "Climate change favors rice production at higher elevations in Colombia," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(8), pages 1401-1430, December.
    5. Xu, Guo-wei & Lu, Da-Ke & Wang, He-Zheng & Li, Youjun, 2018. "Morphological and physiological traits of rice roots and their relationships to yield and nitrogen utilization as influenced by irrigation regime and nitrogen rate," Agricultural Water Management, Elsevier, vol. 203(C), pages 385-394.
    6. Rowshon, M.K. & Dlamini, N.S. & Mojid, M.A. & Adib, M.N.M. & Amin, M.S.M. & Lai, S.H., 2019. "Modeling climate-smart decision support system (CSDSS) for analyzing water demand of a large-scale rice irrigation scheme," Agricultural Water Management, Elsevier, vol. 216(C), pages 138-152.
    7. Fei Wang & Yaning Chen & Zhi Li & Gonghuan Fang & Yupeng Li & Zhenhua Xia, 2019. "Assessment of the Irrigation Water Requirement and Water Supply Risk in the Tarim River Basin, Northwest China," Sustainability, MDPI, Open Access Journal, vol. 11(18), pages 1-16, September.
    8. Feng Huang & Baoguo Li, 2020. "What is the Redline Water Withdrawal for Crop Production in China?—Projection to 2030 Derived from the Past Twenty-Year Trajectory," Sustainability, MDPI, Open Access Journal, vol. 12(10), pages 1-14, May.
    9. Yujie Liu & Weimo Zhou & Quansheng Ge, 2019. "Spatiotemporal changes of rice phenology in China under climate change from 1981 to 2010," Climatic Change, Springer, vol. 157(2), pages 261-277, November.
    10. Pan, Junfeng & Liu, Yanzhuo & Zhong, Xuhua & Lampayan, Rubenito M. & Singleton, Grant R. & Huang, Nongrong & Liang, Kaiming & Peng, Bilin & Tian, Ka, 2017. "Grain yield, water productivity and nitrogen use efficiency of rice under different water management and fertilizer-N inputs in South China," Agricultural Water Management, Elsevier, vol. 184(C), pages 191-200.
    11. Hui Ju & Qin Liu & Yingchun Li & Xiaoxu Long & Zhongwei Liu & Erda Lin, 2020. "Multi-Stakeholder Efforts to Adapt to Climate Change in China’s Agricultural Sector," Sustainability, MDPI, Open Access Journal, vol. 12(19), pages 1-16, September.
    12. Han, Huanhao & Cui, Yuanlai & Huang, Ying & Wang, Shupeng & Duan, Qicai & Zhang, Lei, 2019. "Impacts of the channel/barrier effect and three-dimensional climate—A case study of rice water requirement and irrigation quota in Yunnan, China," Agricultural Water Management, Elsevier, vol. 212(C), pages 317-327.
    13. Hong, Eun-Mi & Nam, Won-Ho & Choi, Jin-Yong & Pachepsky, Yakov A., 2016. "Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea," Agricultural Water Management, Elsevier, vol. 165(C), pages 163-180.
    14. Ding, Yimin & Wang, Weiguang & Zhuang, Qianlai & Luo, Yufeng, 2020. "Adaptation of paddy rice in China to climate change: The effects of shifting sowing date on yield and irrigation water requirement," Agricultural Water Management, Elsevier, vol. 228(C).

  9. Li, Yong & Yang, Jie & Song, Jian, 2015. "Microscale characterization of coupled degradation mechanism of graded materials in lithium batteries of electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1445-1461.

    Cited by:

    1. Li, Yong & Yang, Jie & Song, Jian, 2015. "Electromagnetic effects model and design of energy systems for lithium batteries with gradient structure in sustainable energy electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 842-851.
    2. Li, Yong & Yang, Jie & Song, Jian, 2017. "Efficient storage mechanisms and heterogeneous structures for building better next-generation lithium rechargeable batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1503-1512.
    3. Li, Yong & Yang, Jie & Song, Jian, 2017. "Structure models and nano energy system design for proton exchange membrane fuel cells in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 160-172.
    4. Li, Yong & Yang, Jie & Song, Jian, 2017. "Nano energy system model and nanoscale effect of graphene battery in renewable energy electric vehicle," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 652-663.
    5. Li, Yong & Yang, Jie & Song, Jian, 2016. "Structural model, size effect and nano-energy system design for more sustainable energy of solid state automotive battery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 685-697.
    6. Li, Yong & Yang, Jie & Song, Jian, 2016. "Nano-energy system coupling model and failure characterization of lithium ion battery electrode in electric energy vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1250-1261.
    7. Li, Yong & Yang, Jie & Song, Jian, 2017. "Design principles and energy system scale analysis technologies of new lithium-ion and aluminum-ion batteries for sustainable energy electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 645-651.
    8. Li, Yong & Yang, Jie & Song, Jian, 2017. "Design structure model and renewable energy technology for rechargeable battery towards greener and more sustainable electric vehicle," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 19-25.
    9. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.

  10. Terence Tai Leung Chong & Yue Ding & Yong Li, 2015. "Executive Stock Option Pricing in China Under Stochastic Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(10), pages 953-960, October.
    See citations under working paper version above.
  11. Li, Yong & Zeng, Tao & Yu, Jun, 2014. "A new approach to Bayesian hypothesis testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 602-612.

    Cited by:

    1. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    2. Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
    3. Li, Yong & Liu, Xiaobin & Zeng, Tao & Yu, Jun, 2018. "A Posterior-Based Wald-Type Statistic for Hypothesis Testing," Economics and Statistics Working Papers 8-2018, Singapore Management University, School of Economics.
    4. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    5. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    6. Zhao, Yan-Yong & Lin, Jin-Guan & Xu, Pei-Rong & Ye, Xu-Guo, 2015. "Orthogonality-projection-based estimation for semi-varying coefficient models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 204-221.
    7. Yong Li & Jun Yu, 2019. "An Improved Bayesian Unit Root Test in Stochastic Volatility Models," Annals of Economics and Finance, Society for AEF, vol. 20(1), pages 103-122, May.
    8. Zhang, Yonghui & Chen, Zhongtian & Li, Yong, 2017. "Bayesian testing for short term interest rate models," Finance Research Letters, Elsevier, vol. 20(C), pages 146-152.
    9. Leung, Melvern & Li, Youwei & Pantelous, Athanasios & Vigne, Samuel, 2019. "Bayesian Value-at-Risk Backtesting: The Case of Annuity Pricing," MPRA Paper 101698, University Library of Munich, Germany.
    10. Chen, Shyh-Wei & Hsu, Chi-Sheng & Xie, Zixong, 2016. "Are there periodically collapsing bubbles in the stock markets? New international evidence," Economic Modelling, Elsevier, vol. 52(PB), pages 442-451.
    11. Jin-Yu Zhang & Zhong-Tian Chen & Yong Li, 2019. "Bayesian Testing for Leverage Effect in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1153-1164, March.

  12. Li Yong & Jie Zhang, 2014. "Bayesian testing for jumps in stochastic volatility models with correlated jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1693-1700, October.

    Cited by:

    1. Jin-Yu Zhang & Zhong-Tian Chen & Yong Li, 2019. "Bayesian Testing for Leverage Effect in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1153-1164, March.

  13. Li, Yong & Huang, Wei-Ping & Zhang, Jie, 2013. "Forecasting volatility in the Chinese stock market under model uncertainty," Economic Modelling, Elsevier, vol. 35(C), pages 231-234.

    Cited by:

    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    3. Westerlund, Joakim & Narayan, Paresh Kumar & Zheng, Xinwei, 2015. "Testing for stock return predictability in a large Chinese panel," Emerging Markets Review, Elsevier, vol. 24(C), pages 81-100.
    4. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
    5. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
    6. Xu, Liao & Gao, Han & Shi, Yukun & Zhao, Yang, 2020. "The heterogeneous volume-volatility relations in the exchange-traded fund market: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 400-408.
    7. Qu, Hui & Chen, Wei & Niu, Mengyi & Li, Xindan, 2016. "Forecasting realized volatility in electricity markets using logistic smooth transition heterogeneous autoregressive models," Energy Economics, Elsevier, vol. 54(C), pages 68-76.
    8. Campos, I. & Cortazar, G. & Reyes, T., 2017. "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, vol. 66(C), pages 194-204.
    9. Manel Hamdi & Walid Chkili, 2019. "An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter?," Working Papers 13, Economic Research Forum, revised 21 Aug 2019.

  14. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.

    Cited by:

    1. Chikashi Tsuji, 2016. "Did the expectations channel work? Evidence from quantitative easing in Japan, 2001–06," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1210996-121, December.
    2. Chikashi Tsuji, 2014. "Did the Stock Market Regime Change after the Inauguration of the New Cabinet in Japan?," Business and Management Horizons, Macrothink Institute, vol. 2(1), pages 98-108, June.
    3. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    4. Hsu, Yuan-Lin & Lin, Shih-Kuei & Hung, Ming-Chin & Huang, Tzu-Hui, 2016. "Empirical analysis of stock indices under a regime-switching model with dependent jump size risks," Economic Modelling, Elsevier, vol. 54(C), pages 260-275.

  15. Jin-Yu Zhang & Yong Li & Zhu-Ming Chen, 2013. "Unit Root Hypothesis in the Presence of Stochastic Volatility, a Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 89-100, January.

    Cited by:

    1. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    2. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.
    3. Thomas Nanfeng Li & Agnès Tourin, 2016. "Optimal pairs trading with time-varying volatility," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 1-29, September.

  16. Li, Yong & Chong, Terence Tai-Leung & Zhang, Jie, 2012. "Testing for a unit root in the presence of stochastic volatility and leverage effect," Economic Modelling, Elsevier, vol. 29(5), pages 2035-2038.

    Cited by:

    1. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    2. Pan, Qi & Li, Yong, 2013. "Testing volatility persistence on Markov switching stochastic volatility models," Economic Modelling, Elsevier, vol. 35(C), pages 45-50.
    3. A. B. M. Rabiul Alam Beg & Sajid Anwar, 2014. "Detecting volatility persistence in GARCH models in the presence of the leverage effect," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2205-2213, December.

  17. Li, Yong & Yu, Jun, 2012. "Bayesian hypothesis testing in latent variable models," Journal of Econometrics, Elsevier, vol. 166(2), pages 237-246.
    See citations under working paper version above.
  18. Jin-Guan Lin & Ji Chen & Yong Li, 2012. "Bayesian Analysis of Student t Linear Regression with Unknown Change-Point and Application to Stock Data Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 203-217, October.

    Cited by:

    1. Shuaimin Kang & Guangying Liu & Howard Qi & Min Wang, 2018. "Bayesian Variance Changepoint Detection in Linear Models with Symmetric Heavy-Tailed Errors," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 459-477, August.

  19. Yong Li & Zhongxin Ni & Jie Zhang, 2011. "An Efficient Stochastic Simulation Algorithm for Bayesian Unit Root Testing in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 237-248, March.

    Cited by:

    1. Jin-Yu Zhang & Yong Li & Zhu-Ming Chen, 2013. "Unit Root Hypothesis in the Presence of Stochastic Volatility, a Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 89-100, January.
    2. Jinyan Zhan & Fan Zhang & Siqi Jia & Xi Chu & Yifan Li, 2018. "Spatial Pattern of Regional Urbanization Efficiency: An Empirical Study of Shanghai," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1277-1291, December.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 7 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (4) 2010-11-27 2011-09-05 2012-08-23 2014-08-02
  2. NEP-ETS: Econometric Time Series (3) 2010-11-27 2012-04-17 2014-08-02
  3. NEP-ORE: Operations Research (2) 2010-11-27 2012-04-17
  4. NEP-AGR: Agricultural Economics (1) 2015-09-05
  5. NEP-CNA: China (1) 2015-04-11
  6. NEP-ENE: Energy Economics (1) 2015-09-05
  7. NEP-SEA: South East Asia (1) 2014-08-02
  8. NEP-TRA: Transition Economics (1) 2015-04-11

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