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The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures

Citations

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Cited by:

  1. Chen, Han & Fei, Yijie & Yu, Jun, 2025. "Multivariate stochastic volatility models based on generalized Fisher transformation," Journal of Econometrics, Elsevier, vol. 251(C).
  2. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
  3. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
  4. Xu, Buyun & Wu, Zhimin, 2025. "Real-time GARCH@CARR: A joint model of returns, realized measure of volatility and current intraday information," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
  5. Yuta Kurose & Yasuhiro Omori, "undated". "Multiple-lock Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1075, CIRJE, Faculty of Economics, University of Tokyo.
  6. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
  7. Yuta Yamauchi & Yasuhiro Omori, 2018. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations," Papers 1809.09928, arXiv.org, revised Mar 2019.
  8. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2017. "Inference on Self‐Exciting Jumps in Prices and Volatility Using High‐Frequency Measures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 504-532, April.
  9. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
  10. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S., 2020. "High-frequency jump tests: Which test should we use?," Journal of Econometrics, Elsevier, vol. 219(2), pages 478-487.
  11. Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019. "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
  12. António Alberto Santos, 2015. "The evolution of the Volatility in Financial Returns: Realized Volatility vs Stochastic Volatility Measures," GEMF Working Papers 2015-10, GEMF, Faculty of Economics, University of Coimbra.
  13. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2017. "Realized stochastic volatility with general asymmetry and long memory," Journal of Econometrics, Elsevier, vol. 199(2), pages 202-212.
  14. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
  15. Shirota, Shinichiro & Omori, Yasuhiro & F. Lopes, Hedibert. & Piao, Haixiang, 2017. "Cholesky realized stochastic volatility model," Econometrics and Statistics, Elsevier, vol. 3(C), pages 34-59.
  16. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
  17. Bekierman Jeremias & Gribisch Bastian, 2016. "Estimating stochastic volatility models using realized measures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 279-300, June.
  18. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
  19. Asai, Manabu & McAleer, Michael & Peiris, Shelton, 2020. "Realized stochastic volatility models with generalized Gegenbauer long memory," Econometrics and Statistics, Elsevier, vol. 16(C), pages 42-54.
  20. António A. F. Santos, 2015. "On the Forecasting of Financial Volatility Using Ultra-High Frequency Data," GEMF Working Papers 2015-17, GEMF, Faculty of Economics, University of Coimbra.
  21. Takeuchi-Nogimori, Asuka, 2017. "An Empirical Analysis of Nikkei 225 Options Using Realized GARCH Models," Economic Review, Hitotsubashi University, vol. 68(2), pages 97-113, April.
  22. Yuta Yamauchi & Yasuhiro Omori, 2016. "Multivariate Stochastic Volatility Model with Realized Volatilities and Pairwise Realized Correlations ," CIRJE F-Series CIRJE-F-1029, CIRJE, Faculty of Economics, University of Tokyo.
  23. Creel, Michael & Kristensen, Dennis, 2015. "ABC of SV: Limited information likelihood inference in stochastic volatility jump-diffusion models," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 85-108.
  24. Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2024. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," Finance Research Letters, Elsevier, vol. 67(PB).
  25. Papantonis Ioannis & Rompolis Leonidas S. & Tzavalis Elias & Agapitos Orestis, 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
  26. Worapree Maneesoonthorn & David T. Frazier & Gael M. Martin, 2024. "Probabilistic Predictions of Option Prices Using Multiple Sources of Data," Papers 2412.00658, arXiv.org.
  27. Asuka Takeuchi-Nogimori, 2012. "An Empirical Analysis of the Nikkei 225 Put Options Using Realized GARCH Models," Global COE Hi-Stat Discussion Paper Series gd12-241, Institute of Economic Research, Hitotsubashi University.
  28. Didit Nugroho & Takayuki Morimoto, 2015. "Estimation of realized stochastic volatility models using Hamiltonian Monte Carlo-Based methods," Computational Statistics, Springer, vol. 30(2), pages 491-516, June.
  29. Worapree Maneesoonthorn & Gael M Martin & Catherine S Forbes, 2018. "Dynamic price jumps: The performance of high frequency tests and measures, and the robustness of inference," Monash Econometrics and Business Statistics Working Papers 17/18, Monash University, Department of Econometrics and Business Statistics.
  30. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
  31. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
  32. Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  33. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
  34. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
  35. Watanabe, Toshiaki & Nakajima, Jouchi, 2024. "High-frequency realized stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 79(C).
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