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Denis Pelletier

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. Robert L. Clark & Denis Pelletier, 2019. "Impact of Defaults in Retirement Saving Plans: Public Employee Plans," NBER Working Papers 26234, National Bureau of Economic Research, Inc.

    Cited by:

    1. Robert L. Clark & Olivia S. Mitchell, 2020. "Target Date Defaults in a Public Sector Retirement Saving Plan," Southern Economic Journal, John Wiley & Sons, vol. 86(3), pages 1133-1149, January.
    2. Laura D. Quinby & Geoffrey Sanzenbacher, 2021. "Do Public Sector Workers Increase Their Outside Savings in Response to Pension Cuts?," Boston College Working Papers in Economics 1023, Boston College Department of Economics.
    3. Robert L. Clark & Denis Pelletier, 2019. "Does Automatic Enrollment Increase Contributions to Supplement Retirement Programs by K-12 and University Employees?," NBER Working Papers 26263, National Bureau of Economic Research, Inc.

  2. Cengiz Tunc & Denis Pelletier, 2013. "Endogenous Life-Cycle Housing Investment and Portfolio Allocation," Working Papers 1345, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

    Cited by:

    1. Natalia Khorunzhina, 2019. "Intratemporal nonseparability between housing and nondurable consumption: evidence from reinvestment in housing stock," CESifo Working Paper Series 7663, CESifo.
    2. Geoffrey Meen & Alexander Mihailov & Yehui Wang, 2016. "Endogenous UK Housing Cycles and the Risk Premium: Understanding the Next Housing Crisis," Economics Discussion Papers em-dp2016-02, Department of Economics, University of Reading.

  3. Zhao, Jieyuan & Goodwin, Barry K. & Pelletier, Denis, 2012. "A New Approach to Investigate Market Integration: a Markov-Switching Autoregressive Model with Time-Varying Transition Probabilities," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124825, Agricultural and Applied Economics Association.

    Cited by:

    1. Isaac Abunyuwah & Henry De-Graft Acquah, 2013. "Modelling non-linear Spatial Market Integration and Equilibrium Processes in Hidden Markov Framework," Journal of Economics and Behavioral Studies, AMH International, vol. 5(8), pages 535-545.

  4. Tejeda, Hernan A. & Goodwin, Barry K. & Pelletier, Denis, 2009. "A State Dependent Regime Switching Model of Dynamic Correlations," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49370, Agricultural and Applied Economics Association.

    Cited by:

    1. Xiaodong Du and Lihong Lu McPhail, 2012. "Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    2. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    3. Tejeda, Hernan A. & Goodwin, Barry K., 2009. "Price Volatility, Nonlinearity, and Asymmetric Adjustments in Corn, Soybean, and Cattle Markets: Implications of Ethanol-Driven (Market) Shocks," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53039, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    4. Hernan A. Tejeda & Barry K. Goodwin, 2014. "Dynamic multiproduct optimal hedging in the soybean complex - do time-varying correlations provide hedging improvements?," Applied Economics, Taylor & Francis Journals, vol. 46(27), pages 3312-3322, September.

  5. Bekkerman, Anton & Pelletier, Denis, 2009. "Basis Volatilities of Corn and Soybean in Spatially Separated Markets: The Effect of Ethanol Demand," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49281, Agricultural and Applied Economics Association.

    Cited by:

    1. Busse, S. & Brümmer, B. & Ihle, R., 2011. "Investigating rapeseed price volatilities in the course of the food crisis," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 46, March.

  6. Peter Christoffersen & Jeremy Berkowitz & Denis Pelletier, 2008. "Evaluating Value-at-Risk Models with Desk-Level Data," CREATES Research Papers 2009-35, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. G. Rigatos & N. Zervos, 2017. "Detection of Mispricing in the Black–Scholes PDE Using the Derivative-Free Nonlinear Kalman Filter," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 1-20, June.
    2. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    3. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    4. Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
    5. 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.
    6. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    7. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    8. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    9. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    10. Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    11. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.
    12. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    13. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    14. Jorge Cruz Lopez & Jeffrey Harris & Christophe Hurlin & Christophe Pérignon, 2017. "CoMargin," Post-Print hal-03579309, HAL.
    15. Sylvain Benoît & Christophe Hurlin & Christophe Pérignon, 2015. "Implied Risk Exposures," Post-Print hal-01485613, HAL.
    16. Evangelos Vasileiou, 2022. "Inaccurate Value at Risk Estimations: Bad Modeling or Inappropriate Data?," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1155-1171, March.
    17. Wied, Dominik & Weiß, Gregor N.F. & Ziggel, Daniel, 2016. "Evaluating Value-at-Risk forecasts: A new set of multivariate backtests," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 121-132.
    18. Denisa Banulescu & Christophe Hurlin & Jeremy Leymarie & O. Scaillet, 2019. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Swiss Finance Institute Research Paper Series 19-48, Swiss Finance Institute.
    19. Salehi , Mahdi & Zamani , Mohammad, 2014. "Market Risk Recognition by Different Models in Listed Banks of Tehran Stock Exchange and OTC," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 9(1), pages 147-176, October.
    20. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    21. Christophe Hurlin & Christophe Pérignon, 2012. "Margin Backtesting," Working Papers halshs-00746274, HAL.
    22. Rosnan, Chotard & Michel, Dacorogna & Marie, Kratz, 2016. "Risk Measure Estimates in Quiet and Turbulent Times:An Empirical Study," ESSEC Working Papers WP1618, ESSEC Research Center, ESSEC Business School.
    23. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    24. Mercadier, Mathieu & Strobel, Frank, 2021. "A one-sided Vysochanskii-Petunin inequality with financial applications," European Journal of Operational Research, Elsevier, vol. 295(1), pages 374-377.
    25. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," Post-Print hal-01386081, HAL.
    26. Lu-Tao Zhao & Li-Na Liu & Zi-Jie Wang & Ling-Yun He, 2019. "Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
    27. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    28. Bayer, Sebastian, 2018. "Combining Value-at-Risk forecasts using penalized quantile regressions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 56-77.
    29. Sander Barendse & Erik Kole & Dick van Dijk, 2023. "Backtesting Value-at-Risk and Expected Shortfall in the Presence of Estimation Error," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 528-568.
    30. Herrera, Rodrigo, 2013. "Energy risk management through self-exciting marked point process," Energy Economics, Elsevier, vol. 38(C), pages 64-76.
    31. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    32. 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.
    33. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Exploiting Spillovers to Forecast Crashes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 936-955, December.
    34. Emese Lazar & Ning Zhang, 2017. "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance icma-dp2017-10, Henley Business School, University of Reading.
    35. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    36. Juan Carlos Escanciano & Pei Pei, 2012. "Pitfalls in Backtesting Historical Simulation VaR Models," CAEPR Working Papers 2012-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    37. Pablo Farías, 2014. "Divulgación del valor en riesgo (VaR) previo a la crisis en el sector bancario espanol," Revista Ad-Minister, Universidad EAFIT, July.
    38. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    39. Kratz, Marie & Lok, Y-H & McNeil, Alexander J., 2016. "Multinomial VaR Backtests: A simple implicit approach to backtesting expected shortfall," ESSEC Working Papers WP1617, ESSEC Research Center, ESSEC Business School.
    40. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    41. Nico Katzke & Chris Garbers, 2015. "Do Long Memory and Asymmetries Matter When Assessing Downside Return Risk?," Working Papers 06/2015, Stellenbosch University, Department of Economics.
    42. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    43. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    44. Huang, Xiaoxia & Ying, Haiyao, 2013. "Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations," Economic Modelling, Elsevier, vol. 30(C), pages 61-66.
    45. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data," Papers 1307.5981, arXiv.org, revised Feb 2015.
    46. Kratz, Marie & Lok, Yen H. & McNeil, Alexander J., 2018. "Multinomial VaR backtests: A simple implicit approach to backtesting expected shortfall," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 393-407.
    47. Michael B. Gordy & Alexander J. McNeil, 2017. "Spectral backtests of forecast distributions with application to risk management," Papers 1708.01489, arXiv.org, revised Jul 2019.
    48. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    49. Betz, Frank & Hautsch, Nikolaus & Peltonen, Tuomas A. & Schienle, Melanie, 2016. "Systemic risk spillovers in the European banking and sovereign network," Working Paper Series in Economics 79, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    50. Liu, Wei & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models," Research in International Business and Finance, Elsevier, vol. 54(C).
    51. Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2012. "The Risk Map: A New Tool for Validating Risk Models," Working Papers halshs-00746273, HAL.
    52. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    53. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    54. 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.
    55. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Revista de Estabilidad Financiera, Banco de España, issue NOV.
    56. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    57. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    58. Duy Duong & Toan Luu Duc Huynh, 2020. "Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-26, December.
    59. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    60. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
    61. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    62. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    63. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying – the case of multivariate GARCH models," Economics Working Paper Series 1517, University of St. Gallen, School of Economics and Political Science.
    64. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
    65. Oliveira, Fernando S. & Ruiz Mora, Carlos, 2023. "Risk management in solar-based power plants with storage: a comparative study," DES - Working Papers. Statistics and Econometrics. WS 38369, Universidad Carlos III de Madrid. Departamento de Estadística.
    66. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    67. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524.
    68. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    69. Nikola Radivojevic & Milena Cvjetkovic & Saša Stepanov, 2016. "The new hybrid value at risk approach based on the extreme value theory," Estudios de Economia, University of Chile, Department of Economics, vol. 43(1 Year 20), pages 29-52, June.
    70. Minhaz-Ul-Haq, 2021. "Measuring Market Risk of Commercial Banks Implementing VaR with Historical Simulation Approach," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(4), pages 1-4.
    71. Borgonovo, Emanuele & Gatti, Stefano, 2013. "Risk analysis with contractual default. Does covenant breach matter?," European Journal of Operational Research, Elsevier, vol. 230(2), pages 431-443.
    72. Auer, Benjamin R., 2016. "How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models," Energy Policy, Elsevier, vol. 98(C), pages 621-628.
    73. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
    74. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    75. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
    76. Durán Santomil, Pablo & Otero González, Luís & Martorell Cunill, Onofre & Merigó Lindahl, José M., 2018. "Backtesting an equity risk model under Solvency II," Journal of Business Research, Elsevier, vol. 89(C), pages 216-222.
    77. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    78. Pang, Li-Ping & Chen, Shuang & Wang, Jin-He, 2015. "Risk management in portfolio applications of non-convex stochastic programming," Applied Mathematics and Computation, Elsevier, vol. 258(C), pages 565-575.
    79. Aramonte, Sirio & Giudice Rodriguez, Marius del & Wu, Jason, 2013. "Dynamic factor Value-at-Risk for large heteroskedastic portfolios," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4299-4309.
    80. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    81. Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
    82. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    83. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    84. Fries, Christian P. & Nigbur, Tobias & Seeger, Norman, 2017. "Displaced relative changes in historical simulation: Application to risk measures of interest rates with phases of negative rates," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 175-198.
    85. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    86. Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Norwegian School of Economics, Department of Business and Management Science.
    87. Jakub Nowotarski & Rafał Weron, 2015. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," Computational Statistics, Springer, vol. 30(3), pages 791-803, September.
    88. Soren Bettels & Sojung Kim & Stefan Weber, 2022. "Multinomial Backtesting of Distortion Risk Measures," Papers 2201.06319, arXiv.org, revised Jan 2024.
    89. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    90. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    91. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, vol. 78(C), pages 14-47.
    92. Małecka Marta, 2021. "Testing for a serial correlation in VaR failures through the exponential autoregressive conditional duration model," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 145-162, March.
    93. Sio Chong U & Jacky So & Deng Ding & Lihong Liu, 2016. "An efficient Fourier expansion method for the calculation of value-at-risk: Contributions of extra-ordinary risks," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-27, March.
    94. Yannick Hoga & Matei Demetrescu, 2023. "Monitoring Value-at-Risk and Expected Shortfall Forecasts," Management Science, INFORMS, vol. 69(5), pages 2954-2971, May.
    95. Georges Tsafack & James Cataldo, 2021. "Backtesting and estimation error: value-at-risk overviolation rate," Empirical Economics, Springer, vol. 61(3), pages 1351-1396, September.
    96. Nikola Radivojević & Nikola V. Ćurčić & Djurdjica Dj. Vukajlović, 2017. "Hull-White’s value at risk model: case study of Baltic equities market," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(5), pages 1023-1041, September.
    97. James Cataldo, 2015. "A framework for assessing comprehensive income risk exposure over varying time horizons," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 819-844, November.
    98. Gerlach, Richard & Abeywardana, Sachin, 2016. "Variational Bayes for assessment of dynamic quantile forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1385-1402.
    99. Thor Pajhede, 2015. "Backtesting Value-at-Risk: A Generalized Markov Framework," Discussion Papers 15-18, University of Copenhagen. Department of Economics.
    100. Ziggel, Daniel & Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2014. "A new set of improved Value-at-Risk backtests," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 29-41.
    101. Leccadito, Arturo & Boffelli, Simona & Urga, Giovanni, 2014. "Evaluating the accuracy of value-at-risk forecasts: New multilevel tests," International Journal of Forecasting, Elsevier, vol. 30(2), pages 206-216.
    102. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    103. Jorge V Pérez-Rodríguez & María Santana-Gallego, 2020. "Modelling tourism receipts and associated risks, using long-range dependence models," Tourism Economics, , vol. 26(1), pages 70-96, February.
    104. Marta Małecka, 2014. "Duration-Based Approach to VaR Independence Backtesting," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(4), pages 627-636, September.
    105. Selma Chaker & Nour Meddahi, 2013. "CoMargin," Staff Working Papers 13-47, Bank of Canada.
    106. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    107. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    108. Araújo Santos, P. & Fraga Alves, M.I., 2013. "Forecasting Value-at-Risk with a duration-based POT method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 295-309.
    109. Asmerilda Hitaj & Cesario Mateus & Ilaria Peri, 2018. "Lambda Value at Risk and Regulatory Capital: A Dynamic Approach to Tail Risk," Risks, MDPI, vol. 6(1), pages 1-18, March.
    110. Buccioli, Alice & Kokholm, Thomas & Nicolosi, Marco, 2019. "Expected shortfall and portfolio management in contagious markets," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 100-115.
    111. Luigi Aldieri & Alessandra Amendola & Vincenzo Candila, 2023. "The Impact of ESG Scores on Risk Market Performance," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    112. Gregor Wei{ss} & Marcus Scheffer, 2012. "Smooth Nonparametric Bernstein Vine Copulas," Papers 1210.2043, arXiv.org.

  7. Alastair R. Hall & Denis Pelletier, 2007. "Non-Nested Testing in Models Estimated via Generalized Method of Moments," Working Paper Series 011, North Carolina State University, Department of Economics, revised Mar 2007.

    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    2. Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Microeconomics.ca working papers vadim_marmer-2008-13, Vancouver School of Economics, revised 25 Jul 2011.
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  9. Denis Pelletier, 2004. "Regime Switching for Dynamic Correlations," Econometric Society 2004 North American Summer Meetings 230, Econometric Society.

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    4. 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".
    5. Jianqing Fan & Mingjin Wang & Qiwei Yao, 2008. "Modelling multivariate volatilities via conditionally uncorrelated components," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 679-702, September.
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    8. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
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    10. Oscar V. De la Torre-Torres & José Álvarez-García & María de la Cruz del Río-Rama, 2024. "An EM/MCMC Markov-Switching GARCH Behavioral Algorithm for Random-Length Lumber Futures Trading," Mathematics, MDPI, vol. 12(3), pages 1-21, February.
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    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.
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    3. DUFOUR, Jean-Marie & PELLETIER, Denis & RENAULT, Éric, 2003. "Short Run and Long Run Causality in Time Series : Inference," Cahiers de recherche 14-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. Jean-Marie Dufour & Tarek Jouini, 2005. "Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing," CIRANO Working Papers 2005s-26, CIRANO.
    5. Zhidong Bai & Yongchang Hui & Dandan Jiang & Zhihui Lv & Wing-Keung Wong & Shurong Zheng, 2018. "A new test of multivariate nonlinear causality," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-14, January.
    6. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    7. Dimitris Christopoulos & Miguel A. León-Ledesma, 2009. "On causal Relationships Between Exchange Rates and Fundamentals: Better Than You Think," Studies in Economics 0909, School of Economics, University of Kent.
    8. Vincent Bouvatier, 2007. "Hot Money Inflows and Monetary Stability in China: How the People's Bank of China Took up the Challenge," Money Macro and Finance (MMF) Research Group Conference 2006 161, Money Macro and Finance Research Group.
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    10. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2020. "Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality," Journal of Econometrics, Elsevier, vol. 218(2), pages 633-654.
    11. Hui Jun ZHANG & Jean-Marie DUFOUR & John W. GALBRAITH, 2013. "Exchange Rates and Commodity Prices : Measuring Causality at Multiple Horizons," Cahiers de recherche 14-2013, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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    20. Stephanie-Carolin Grosche, 2014. "What Does Granger Causality Prove? A Critical Examination of the Interpretation of Granger Causality Results on Price Effects of Index Trading in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 279-302, June.
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    22. Krätschell, Karoline & Schmidt, Torsten, 2013. "Long-run trends or short-run fluctuations What establishes the correlation between oil and food prices?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79798, Verein für Socialpolitik / German Economic Association.
    23. Costas Milas & Theodore Panagiotidis & Theologos Dergiades, 2021. "Does It Matter Where You Search? Twitter versus Traditional News Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(7), pages 1757-1795, October.
    24. Konstantakis, Konstantinos N. & Papageorgiou, Theofanis & Christopoulos, Apostolos G. & Dokas, Ioannis G. & Michaelides, Panayotis G., 2017. "Business cycles in Greek maritime transport: an econometric exploration (1998–2015)," LSE Research Online Documents on Economics 83540, London School of Economics and Political Science, LSE Library.
    25. Jeffrey E. Jarrett & Xia Pan & Shaw Chen, 2009. "Do the Chinese Bourses (Stock Markets) Predict Economic Growth?," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(3), pages 201-211, December.
    26. Tomasz Wozniak, 2012. "Testing Causality Between Two Vectors in Multivariate GARCH Models," Department of Economics - Working Papers Series 1139, The University of Melbourne.
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    29. Dietmar Bauer & Alex Maynard, 2010. "Persistence-robust Granger causality testing," Working Papers 1011, University of Guelph, Department of Economics and Finance.
    30. 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.
    31. Karoline Krätschell & Torsten Schmidt, 2017. "Long-run waves or short-run fluctuations – what establishes the correlation between oil and food prices?," Applied Economics, Taylor & Francis Journals, vol. 49(54), pages 5535-5546, November.
    32. Lemmens, Aurélie & Croux, Christophe & Dekimpe, Marnik G., 2008. "Measuring and testing Granger causality over the spectrum: An application to European production expectation surveys," International Journal of Forecasting, Elsevier, vol. 24(3), pages 414-431.
    33. Fanelli, Luca & Paruolo, Paolo, 2007. "Speed of Adjustment in Cointegrated Systems," MPRA Paper 9174, University Library of Munich, Germany.
    34. Matthieu Droumaguet & Tomasz Wozniak, 2012. "Bayesian Testing of Granger Causality in Markov-Switching VARs," Economics Working Papers ECO2012/06, European University Institute.
    35. Krätschell, Karoline & Schmidt, Torsten, 2012. "Long-run Trends or Short-run Fluctuations – What Establishes the Correlation between Oil and Food Prices?The Interplay of Standardized Tests and Incentives – An Econometric Analysis with Data from PIS," Ruhr Economic Papers 357, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    36. Ke-Li Xu, 2022. "On Local Projection Based Inference," CAEPR Working Papers 2022-002 Classification-, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    37. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2016. "Oil price and exchange rate in India: Fresh evidence from continuous wavelet approach and asymmetric, multi-horizon Granger-causality tests," Applied Energy, Elsevier, vol. 179(C), pages 272-283.
    38. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
    39. Salamaliki, Paraskevi K. & Venetis, Ioannis A., 2013. "Energy consumption and real GDP in G-7: Multi-horizon causality testing in the presence of capital stock," Energy Economics, Elsevier, vol. 39(C), pages 108-121.
    40. Ciner, Cetin, 2007. "Dynamic linkages between international bond markets," Journal of Multinational Financial Management, Elsevier, vol. 17(4), pages 290-303, October.
    41. Ralf Brüggemann & Christian Kascha, 2017. "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz 2017-06, Department of Economics, University of Konstanz.
    42. Jonathan B. Hill, 2004. "Efficient Tests of Long-Run Causation in Trivariate VAR Processes with a Rolling Window Study of the Money-Income Relationship," Macroeconomics 0407013, University Library of Munich, Germany, revised 15 Feb 2006.
    43. Paraskevi Salamaliki & Ioannis Venetis & Nicholas Giannakopoulos, 2013. "The causal relationship between female labor supply and fertility in the USA: updated evidence via a time series multi-horizon approach," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(1), pages 109-145, January.
    44. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2015. "Testing for Granger causality in large mixed-frequency VARs," Discussion Papers 45/2015, Deutsche Bundesbank.
    45. Yener Coskun & Christos Bouras & Rangan Gupta & Mark E. Wohar, 2021. "Multi-Horizon Financial and Housing Wealth Effects across the U.S. States," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    46. Dudda, Tom L. & Klein, Tony & Nguyen, Duc Khuong & Walther, Thomas, 2022. "Common Drivers of Commodity Futures?," QBS Working Paper Series 2022/05, Queen's University Belfast, Queen's Business School.
    47. Breitung, Jorg & Candelon, Bertrand, 2006. "Testing for short- and long-run causality: A frequency-domain approach," Journal of Econometrics, Elsevier, vol. 132(2), pages 363-378, June.
    48. Costas Milas & Theodore Panagiotidis & Theologos Dergiades, 2018. "Twitter versus Traditional News Media: Evidence for the Sovereign Bond Markets," Working Paper series 18-42, Rimini Centre for Economic Analysis.
    49. Ren, Yunwen & Xiao, Zhiguo & Zhang, Xinsheng, 2013. "Two-step adaptive model selection for vector autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 349-364.
    50. Ke-Li Xu, 2023. "Local Projection Based Inference under General Conditions," CAEPR Working Papers 2023-001 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    51. Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2023. "Directed graphs and variable selection in large vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 223-246, March.
    52. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    53. Apergis, Nicholas & Bouras, Christos & Christou, Christina & Hassapis, Christis, 2018. "Multi-horizon wealth effects across the G7 economies," Economic Modelling, Elsevier, vol. 72(C), pages 165-176.
    54. Yiannis Kamarianakis & Vagelis Kaslis, 2005. "Geographical competition-complementarity relationships between Greek regional economies," ERSA conference papers ersa05p552, European Regional Science Association.
    55. Judith A. Clarke & Mukesh Ralhan, 2005. "Direct and Indirect Causality Between Exports and Economic Output for Bangladesh and Sri Lanka: Horizon Matters," Econometrics Working Papers 0512, Department of Economics, University of Victoria.
    56. Majid M. Al-Sadoon, 2016. "Testing Subspace Granger Causality," Working Papers 850, Barcelona School of Economics.
    57. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    58. Lei Pan & Svetlana Maslyuk-Escobedo & Vinod Mishra, 2019. "Carry Trade Returns and Commodity Prices under Capital and Interest Rate Controls: Empirical Evidence from China," Monash Economics Working Papers 16-18, Monash University, Department of Economics.
    59. Jonathan B. Hill, 2004. "Causation Delays and Causal Neutralization for General Horizons: The Money-Output Relationship Revisited," Econometrics 0402002, University Library of Munich, Germany, revised 23 Mar 2005.
    60. 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.
    61. Vincent Bouvatier, 2006. "Hot money inflows in China: How the people's bank of China took up the challenge," Cahiers de la Maison des Sciences Economiques bla06011, Université Panthéon-Sorbonne (Paris 1).
    62. Patrick Withey, 2014. "Energy Use, Income and Carbon Dioxide Emissions: Direct and Multi-Horizon Causality in Canada," International Journal of Energy Economics and Policy, Econjournals, vol. 4(2), pages 178-188.
    63. Jonathan B. Hill, 2005. "Causation Delays and Causal Neutralization up to Three Steps Ahead: The Money-Output Relationship Revisited," Econometrics 0503016, University Library of Munich, Germany, revised 23 Mar 2005.
    64. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2013. "Testing for Granger Causality with Mixed Frequency Data," CEPR Discussion Papers 9655, C.E.P.R. Discussion Papers.
    65. Mardi Dungey & Stan Hurn & Shuping Shi & Vladimir Volkov, 2019. "Information Flow in Times of Crisis: The Case of the European Banking and Sovereign Sectors," Econometrics, MDPI, vol. 7(1), pages 1-20, January.
    66. Konstantinos N. Konstantakis & Panayotis G. Michaelides, 2015. "Step-by-Step Causality Revisited: Theory and Evidence," Economics Bulletin, AccessEcon, vol. 35(2), pages 871-877.
    67. Mounir Belloumi & Atef Saad Alshehry, 2015. "Sustainable Energy Development in Saudi Arabia," Sustainability, MDPI, vol. 7(5), pages 1-18, April.
    68. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    69. Dufour, Jean-Marie & Jouini, Tarek, 2006. "Finite-sample simulation-based inference in VAR models with application to Granger causality testing," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 229-254.
    70. François-Éric Racicota & David Tessierc, 2023. "On the relationship between Jorda?s IRF local projection and Dufour et al.?s robust (p,h)-autoregression multihorizon causality: a note," Working Papers 2023-001, Department of Research, Ipag Business School.
    71. Judith A. Clarke & Nilanjana Roy & Weichun Chen, 2012. "Health and Wealth: Short Panel Granger Causality Tests for Developing Countries," Econometrics Working Papers 1204, Department of Economics, University of Victoria.
    72. Daglis, Theodoros & Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2019. "Solar events and economic activity: Evidence from the US Telecommunications industry (1996–2014)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    73. Hsiu-Hsin Ko, 2015. "On the indirect causality relation from exchange rates to fundamentals," Economics Bulletin, AccessEcon, vol. 35(3), pages 1518-1524.
    74. André, NYEMBWE & Konstantin, KHOLODILIN, 2005. "North-South Asymmetric Relationships : Does the EMU Business Affect Small African Economies ?," Discussion Papers (ECON - Département des Sciences Economiques) 2005032, Université catholique de Louvain, Département des Sciences Economiques.
    75. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Short and long run causality measures: Theory and inference," Journal of Econometrics, Elsevier, vol. 154(1), pages 42-58, January.
    76. Ioanna Konstantakopoulou, 2017. "The aggregate exports-GDP relation under the prism of infrequent trend breaks and multi-horizon causality," International Economics and Economic Policy, Springer, vol. 14(4), pages 661-689, October.
    77. Matthieu Droumaguet & Anders Warne & Tomasz Wozniak, 2015. "Granger Causality and Regime Inference in Bayesian Markov-Switching VARs," Department of Economics - Working Papers Series 1191, The University of Melbourne.
    78. Daglis, Theodoros & Yfanti, Stavroula & Xidonas, Panos & Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2023. "Does solar activity affect the price of crude oil? A causality and volatility analysis," Finance Research Letters, Elsevier, vol. 55(PA).
    79. Heaton, Chris, 2015. "Testing for multiple-period predictability between serially dependent time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 587-597.
    80. Bosupeng, Mpho, 2014. "Sensitivity Of Stock Prices To Money Supply Dynamics," MPRA Paper 77924, University Library of Munich, Germany, revised 2014.
    81. Gurleen Sahota & Balwinder Singh, 2016. "The Empirical Investigation of Causal Relationship between Intraday Return and Volume in Indian Stock Market," Vision, , vol. 20(3), pages 199-210, September.
    82. Grosche, Stephanie, 2012. "Limitations of Granger Causality Analysis to assess the price effects from the financialization of agricultural commodity markets under bounded rationality," Discussion Papers 121868, University of Bonn, Institute for Food and Resource Economics.
    83. Haoke Ding & Yinghua Ren & Wanhai You, 2022. "Does uncertainty granger-causes visitor arrivals? evidence from the MF-VAR model," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4193-4215, December.

  12. Saphores, J.D. & Khalaf, L. & Pelletier, D., 2000. "On Jumps and ARCH Effects in Natural Resource Prices. An Application to Stumpage Prices from Pacific Northwest National Forests," Papers 00-03, Laval - Recherche en Energie.

    Cited by:

    1. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien McMahon, 2006. "Forecasting Commodity Prices: GARCH, Jumps, and Mean Reversion," Staff Working Papers 06-14, Bank of Canada.
    2. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-Francois, 2003. "Simulation-based exact jump tests in models with conditional heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 28(3), pages 531-553, December.
    3. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian, 2004. "Structural Change and Forecasting Long-Run Energy Prices," Staff Working Papers 04-5, Bank of Canada.
    4. Khalaf, Lynda & Kichian, Maral, 2005. "Exact tests of the stability of the Phillips curve: the Canadian case," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 445-460, April.
    5. Hultkrantz, Lars & Andersson, Linda & Mantalos, Panagiotis, 2014. "Stumpage prices in Sweden 1909–2012: Testing for non-stationarity," Journal of Forest Economics, Elsevier, vol. 20(1), pages 33-46.
    6. Andersson, Linda & Hultkrantz , Lars & Mantalos , Panagiotis, 2013. "Stumpage Prices in Sweden 1909-2011: Testing for Non-Stationarity," Working Papers 2013:1, Örebro University, School of Business.
    7. Lee, Yen-Hsien & Hu, Hsu-Ning & Chiou, Jer-Shiou, 2010. "Jump dynamics with structural breaks for crude oil prices," Energy Economics, Elsevier, vol. 32(2), pages 343-350, March.

Articles

  1. Atsushi Inoue & Lu Jin & Denis Pelletier, 2021. "Local-Linear Estimation of Time-Varying-Parameter GARCH Models and Associated Risk Measures [Modelling Volatility by Variance Decomposition]," Journal of Financial Econometrics, Oxford University Press, vol. 19(1), pages 202-234.

    Cited by:

    1. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    2. 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.
    3. 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.

  2. Denis Pelletier & Cengiz Tunc, 2019. "Endogenous Life‐Cycle Housing Investment and Portfolio Allocation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(4), pages 991-1019, June.
    See citations under working paper version above.
  3. Krishnamurthy, Srinivasan & Pelletier, Denis & Warr, Richard S., 2018. "Inflation and equity mutual fund flows," Journal of Financial Markets, Elsevier, vol. 37(C), pages 52-69.

    Cited by:

    1. Ghozali Maski & An'im Kafabih & Arif Hoetoro, 2018. "Testing Profit and Loss Sharing to Stabilise Level of Inflation: Evidence From Indonesia," Research in World Economy, Research in World Economy, Sciedu Press, vol. 9(2), pages 12-23, June.
    2. Rakowski, David & Yamani, Ehab, 2021. "Endogeneity in the mutual fund flow–performance relationship: An instrumental variables solution," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 247-271.

  4. Robert L. Clark & Aditi Pathak & Denis Pelletier, 2018. "Supplemental Retirement Savings Plans in the Public Sector: Participation and Contribution Decisions by School Personnel," Journal of Labor Research, Springer, vol. 39(4), pages 383-404, December.

    Cited by:

    1. Nino Abashidze & Robert L. Clark & Beth Ritter & David Vanderweide, 2018. "Annuity Pricing in Public Pension Plans: Importance of Interest Rates," NBER Working Papers 25343, National Bureau of Economic Research, Inc.
    2. Robert L. Clark & Denis Pelletier, 2019. "Impact of Defaults in Retirement Saving Plans: Public Employee Plans," NBER Working Papers 26234, National Bureau of Economic Research, Inc.
    3. Robert L. Clark & Denis Pelletier, 2019. "Does Automatic Enrollment Increase Contributions to Supplement Retirement Programs by K-12 and University Employees?," NBER Working Papers 26263, National Bureau of Economic Research, Inc.
    4. Robert L. Clark & Robert G. Hammond & Christelle Khalaf & Melinda Sandler Morrill, 2017. "Planning for Retirement? The Importance of Time Preferences," NBER Working Papers 23501, National Bureau of Economic Research, Inc.

  5. Denis Pelletier & Wei Wei, 2016. "The Geometric-VaR Backtesting Method," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 725-745.

    Cited by:

    1. Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
    2. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
    3. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    4. S. M. Masrur Ahmed, 2023. "Sizing Strategies for Algorithmic Trading in Volatile Markets: A Study of Backtesting and Risk Mitigation Analysis," Papers 2309.09094, arXiv.org, revised Sep 2023.
    5. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    6. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    7. Małecka Marta, 2021. "Testing for a serial correlation in VaR failures through the exponential autoregressive conditional duration model," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 145-162, March.

  6. Hall, Alastair R. & Pelletier, Denis, 2011. "Nonnested Testing In Models Estimated Via Generalized Method Of Moments," Econometric Theory, Cambridge University Press, vol. 27(2), pages 443-456, April.
    See citations under working paper version above.
  7. Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011. "Evaluating Value-at-Risk Models with Desk-Level Data," Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
    See citations under working paper version above.
  8. McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.

    Cited by:

    1. Li, Junye, 2013. "An unscented Kalman smoother for volatility extraction: Evidence from stock prices and options," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 15-26.
    2. Alessia Naccarato & Andrea Pierini & Giovanna Ferraro, 2021. "Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment," Annals of Operations Research, Springer, vol. 299(1), pages 81-99, April.
    3. Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Joshua C.C. Chan & Rodney Strachan, 2014. "The Zero Lower Bound: Implications for Modelling the Interest Rate," Working Paper series 42_14, Rimini Centre for Economic Analysis.
    5. Angelia L. Grant & Joshua C.C. Chan, 2017. "A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(2-3), pages 525-552, March.
    6. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    7. Agbeyegbe, Terence D., 2020. "Bayesian analysis of output gap in Barbados," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    8. Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
    9. Chan, Joshua C.C. & Santi, Caterina, 2021. "Speculative bubbles in present-value models: A Bayesian Markov-switching state space approach," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    10. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
    11. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    12. Kastner, Gregor, 2016. "Dealing with Stochastic Volatility in Time Series Using the R Package stochvol," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i05).
    13. Delle Monache, Davide & Petrella, Ivan, 2019. "Efficient Matrix Approach for Classical Inference in State Space Models," EMF Research Papers 19, Economic Modelling and Forecasting Group.
    14. Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.
    15. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    16. Joshua Chan & Rodney Strachan, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," CAMA Working Papers 2012-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    18. Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
    19. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    20. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    21. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    22. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    23. Jan van den Brakel & Martijn Souren & Sabine Krieg, 2022. "Estimating monthly labour force figures during the COVID‐19 pandemic in the Netherlands," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1560-1583, October.
    24. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
    25. Pettenuzzo, Davide & Sabbatucci, Riccardo & Timmermann, Allan, 2023. "Dividend suspensions and cash flows during the Covid-19 pandemic: A dynamic econometric model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1522-1541.
    26. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    27. Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper series 43_14, Rimini Centre for Economic Analysis.
    28. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    29. Terence D. Agbeyegbe, 2023. "The Link Between Output Growth and Output Growth Volatility: Barbados," Annals of Data Science, Springer, vol. 10(3), pages 787-804, June.
    30. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    31. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    32. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    33. Hong, Bingyuan & Li, Xiaoping & Li, Yu & Chen, Shilin & Tan, Yao & Fan, Di & Song, Shangfei & Zhu, Baikang & Gong, Jing, 2022. "An improved hydraulic model of gathering pipeline network integrating pressure-exchange ejector," Energy, Elsevier, vol. 260(C).
    34. Martin Iseringhausen, 2018. "The Time-Varying Asymmetry Of Exchange Rate Returns: A Stochastic Volatility – Stochastic Skewness Model," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 18/944, Ghent University, Faculty of Economics and Business Administration.
    35. David E. Allen & Michael McAleer, 2020. "Do We Need Stochastic Volatility and Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns on FTSE," Risks, MDPI, vol. 8(1), pages 1-20, February.
    36. Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
    37. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2022. "Understanding trend inflation through the lens of the goods and services sectors," CAMA Working Papers 2022-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    38. Peter Knaus & Sylvia Fruhwirth-Schnatter, 2023. "The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models," Papers 2312.10487, arXiv.org.
    39. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    40. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    41. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    42. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
    43. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    44. Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    45. Peter Knaus & Angela Bitto-Nemling & Annalisa Cadonna & Sylvia Fruhwirth-Schnatter, 2019. "Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP," Papers 1907.07065, arXiv.org, revised Nov 2020.
    46. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    47. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2018. "Modeling volatility dynamics using non-Gaussian stochastic volatility model based on band matrix routine," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 193-201.
    48. 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.
    49. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    50. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    51. Darjus Hosszejni & Gregor Kastner, 2019. "Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage," Papers 1901.11491, arXiv.org, revised Nov 2019.
    52. Cross, Jamie L. & Hou, Chenghan & Trinh, Kelly, 2021. "Returns, volatility and the cryptocurrency bubble of 2017–18," Economic Modelling, Elsevier, vol. 104(C).
    53. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    54. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    55. Joshua C.C. Chan & Eric Eisenstat, 2013. "Gibbs Samplers for VARMA and Its Extensions," ANU Working Papers in Economics and Econometrics 2013-604, Australian National University, College of Business and Economics, School of Economics.
    56. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The volatility effect on precious metals price returns in a stochastic volatility in mean model with time-varying parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    57. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    58. Osman Doğan & Süleyman Taşpınar & Anil K. Bera, 2021. "Bayesian estimation of stochastic tail index from high-frequency financial data," Empirical Economics, Springer, vol. 61(5), pages 2685-2711, November.
    59. Carlos A. Abanto-Valle & Hernán B. Garrafa-Aragón, 2019. "Threshold Stochastic Volatility Models with Heavy Tails:A Bayesian Approach," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(83), pages 32-53.
    60. Grant, Angelia L., 2018. "The Great Recession and Okun's law," Economic Modelling, Elsevier, vol. 69(C), pages 291-300.

  9. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    See citations under working paper version above.
  10. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    See citations under working paper version above.
  11. Peter Christoffersen, 2004. "Backtesting Value-at-Risk: A Duration-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 84-108.
    See citations under working paper version above.
  12. Jean-Daniel Saphores & Lynda Khalaf & Denis Pelletier, 2002. "On Jumps and ARCH Effects in Natural Resource Prices: An Application to Pacific Northwest Stumpage Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 387-400.

    Cited by:

    1. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien McMahon, 2006. "Forecasting Commodity Prices: GARCH, Jumps, and Mean Reversion," Staff Working Papers 06-14, Bank of Canada.
    2. Saphores, Jean-Daniel & Vincent, Jeffrey R. & Marochko, Valy & Abrudan, Ioan & Bouriaud, Laura & Zinnes, Clifford, 2006. "Detecting collusion in timber auctions : an application to Romania," Policy Research Working Paper Series 4105, The World Bank.
    3. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-Francois, 2003. "Simulation-based exact jump tests in models with conditional heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 28(3), pages 531-553, December.
    4. Rajendra Prasad Khajuria & Shashi Kant & Susanna Laaksonen-Craig, 2009. "Valuation of Timber Harvesting Options Using a Contingent Claims Approach," Land Economics, University of Wisconsin Press, vol. 85(4), pages 655-674.
    5. Chen, Shan & Insley, Margaret, 2012. "Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 201-219.
    6. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian, 2004. "Structural Change and Forecasting Long-Run Energy Prices," Staff Working Papers 04-5, Bank of Canada.
    7. Creamer, Selmin F. & Genz, Alan & Blatner, Keith A., 2012. "The Effect of Fire Risk on the Critical Harvesting Times for Pacific Northwest Douglas-Fir When Carbon Price Is Stochastic," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 41(3), pages 1-14, December.
    8. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2018. "The volatility effect on precious metals prices in a stochastic volatility in mean model with time-varying parameters," Working Papers 15-34, Eastern Mediterranean University, Department of Economics.
    9. McGough, Bruce & Plantinga, Andrew J. & Provencher, Bill, 2002. "The Dynamic Behavior Of Efficient Timber Prices," Staff Papers 12607, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    10. Khalaf, Lynda & Kichian, Maral, 2005. "Exact tests of the stability of the Phillips curve: the Canadian case," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 445-460, April.
    11. Work, J. & Qiu, F. & Luckert, M.K., 2016. "Examining hardwood pulp and ethanol prices for improved poplar plantations in Canada," Forest Policy and Economics, Elsevier, vol. 70(C), pages 9-15.
    12. Hellström, Jörgen & Lundgren, Jens & Yu, Haishan, 2012. "Why do electricity prices jump? Empirical evidence from the Nordic electricity market," Energy Economics, Elsevier, vol. 34(6), pages 1774-1781.
    13. Tsai, Mei-Ting & Saphores, Jean-Daniel & Regan, Amelia, 2011. "Valuation of freight transportation contracts under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 920-932.
    14. Lee, Yen-Hsien & Hu, Hsu-Ning & Chiou, Jer-Shiou, 2010. "Jump dynamics with structural breaks for crude oil prices," Energy Economics, Elsevier, vol. 32(2), pages 343-350, March.
    15. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The volatility effect on precious metals price returns in a stochastic volatility in mean model with time-varying parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).

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