IDEAS home Printed from https://ideas.repec.org/f/pis204.html

Tsunehiro Ishihara

Personal Details

First Name:Tsunehiro
Middle Name:
Last Name:Ishihara
Suffix:
In ASCII letters:
RePEc Short-ID:pis204
[This author has chosen not to make the email address public]
https://sites.google.com/site/tsunehiroishihara/

Affiliation

Osaka University of Economics

Osaka, Japan
http://www.osaka-ue.ac.jp/
RePEc:edi:osuecjp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
  2. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Multivariate Stochastic Volatility with Cross Leverage," CARF F-Series CARF-F-191, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  3. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  4. Tsunehiro Ishihara & Yasuhiro Omori, 2008. ""Markov Switching Asymmetric Stochastic Volatility Model with Application to TOPIX Data -A Permutation Sampler Approach-"(in Japanese)," CIRJE J-Series CIRJE-J-191, CIRJE, Faculty of Economics, University of Tokyo.
  5. Tsunehiro Ishihara & Yasuhiro Omori, 2008. "Markov Switching Asymmetric Stochastic Volatility Model with Application to TOPIX Data -A Permutation Sampler Approach-," CARF J-Series CARF-J-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

Articles

  1. Tsunehiro Ishihara & Yasuhiro Omori, 2017. "Portfolio optimization using dynamic factor and stochastic volatility: evidence on Fat-tailed errors and leverage," The Japanese Economic Review, Japanese Economic Association, vol. 68(1), pages 63-94, March.
  2. Ishihara, Tsunehiro & Omori, Yasuhiro & Asai, Manabu, 2016. "Matrix exponential stochastic volatility with cross leverage," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 331-350.
  3. Ishihara, Tsunehiro & Watanabe, Toshiaki, 2015. "Econometric Analysis of Business Cycles: A Survey with the Application to the Composite Index in Japan," Economic Review, Hitotsubashi University, vol. 66(2), pages 145-168, April.
  4. Ishihara, Tsunehiro, 2015. "Estimation of Generalized Realized Stochastic Volatility Model: An Application to Calendar Effect of Nikkei 225," Economic Review, Hitotsubashi University, vol. 66(1), pages 1-18, January.
  5. Ishihara, Tsunehiro & Omori, Yasuhiro, 2012. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3674-3689.

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. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-953, CIRJE, Faculty of Economics, University of Tokyo.
    2. Ilya Archakov & Peter Reinhard Hansen & Asger Lunde, 2020. "A Multivariate Realized GARCH Model," Papers 2012.02708, arXiv.org, revised Feb 2025.
    3. Yuta Kurose, 2021. "Stochastic volatility model with range-based correction and leverage," Papers 2110.00039, arXiv.org, revised Oct 2021.
    4. Manabu Asai & Michael McAleer, 2022. "Bayesian Analysis of Realized Matrix-Exponential GARCH Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 103-123, January.
    5. Asai, M. & Chang, C-L. & McAleer, M.J., 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Econometric Institute Research Papers EI2016-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Chen, Han & Fei, Yijie & Yu, Jun, 2025. "Multivariate stochastic volatility models based on generalized Fisher transformation," Journal of Econometrics, Elsevier, vol. 251(C).
    7. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    8. Ewa Feder-Sempach & Piotr Szczepocki & Joanna Bogołębska, 2024. "Global uncertainty and potential shelters: gold, bitcoin, and currencies as weak and strong safe havens for main world stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    9. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Working Papers in Economics 14/10, University of Canterbury, Department of Economics and Finance.
    10. Jouchi Nakajima, 2017. "Bayesian analysis of multivariate stochastic volatility with skew return distribution," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 546-562, May.
    11. Ishihara, Tsunehiro & Omori, Yasuhiro & Asai, Manabu, 2016. "Matrix exponential stochastic volatility with cross leverage," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 331-350.
    12. Yuta Kurose & Yasuhiro Omori, 2014. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-941, CIRJE, Faculty of Economics, University of Tokyo.
    13. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-1019, CIRJE, Faculty of Economics, University of Tokyo.
    14. Ilya Archakov & Peter Reinhard Hansen, 2020. "A New Parametrization of Correlation Matrices," Papers 2012.02395, arXiv.org.
    15. Han Chen & Yijie Fei & Jun Yu, 2026. "Multivariate Stochastic Volatility Model with Block Correlations," Working Papers 202638, University of Macau, Faculty of Business Administration.
    16. Khoo, Zhi De & Ng, Kok Haur & Koh, You Beng & Ng, Kooi Huat, 2025. "Forecasting financial volatility: An approach based on Parkinson volatility measure with long memory stochastic range model," Journal of Empirical Finance, Elsevier, vol. 82(C).
    17. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    18. Wu, Xinyu & Wang, Xiaona, 2020. "Forecasting volatility using realized stochastic volatility model with time-varying leverage effect," Finance Research Letters, Elsevier, vol. 34(C).
    19. Tian, Shuairu & Hamori, Shigeyuki, 2015. "Modeling interest rate volatility: A Realized GARCH approach," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 158-171.
    20. Trojan, Sebastian, 2014. "Multivariate Stochastic Volatility with Dynamic Cross Leverage," Economics Working Paper Series 1424, University of St. Gallen, School of Economics and Political Science.

  2. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Multivariate Stochastic Volatility with Cross Leverage," CARF F-Series CARF-F-191, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Cited by:

    1. Diks, Cees & Panchenko, Valentyn & Sokolinskiy, Oleg & van Dijk, Dick, 2014. "Comparing the accuracy of multivariate density forecasts in selected regions of the copula support," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 79-94.
    2. Skaug, Hans J. & Yu, Jun, 2014. "A flexible and automated likelihood based framework for inference in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 642-654.
    3. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    4. Asai, Manabu & Caporin, Massimiliano & McAleer, Michael, 2015. "Forecasting Value-at-Risk using block structure multivariate stochastic volatility models," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 40-50.
    5. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CIRJE F-Series CIRJE-F-742, CIRJE, Faculty of Economics, University of Tokyo.
    6. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    7. Caporin, Massimiliano, 2013. "Equity and CDS sector indices: Dynamic models and risk hedging," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 261-275.
    8. Manabu Asai & Michael McAleer, 2017. "A fractionally integrated Wishart stochastic volatility model," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 42-59, March.
    9. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    10. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
    11. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    12. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    13. Ishihara, Tsunehiro & Omori, Yasuhiro & Asai, Manabu, 2016. "Matrix exponential stochastic volatility with cross leverage," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 331-350.
    14. Mustafa Hakan Eratalay, 2012. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," EUSP Department of Economics Working Paper Series 2012/04, European University at St. Petersburg, Department of Economics.
    15. Kurose, Yuta & Omori, Yasuhiro, 2016. "Dynamic equicorrelation stochastic volatility," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 795-813.
    16. Tsunehiro Ishihara & Yasuhiro Omori, 2010. "Efficient Bayesian Estimation of a Multivariate Stochastic Volatility Model with Cross Leverage and Heavy-Tailed Errors," CIRJE F-Series CIRJE-F-746, CIRJE, Faculty of Economics, University of Tokyo.
    17. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Caldeira, João F & Moura, Guilherme Valle & Santos, André Alves Portela, 2013. "Seleção de carteiras utilizando o modelo Fama-French-Carhart," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    19. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    20. Luger, Richard, 2025. "Regularizing stock return covariance matrices via multiple testing of correlations," Journal of Econometrics, Elsevier, vol. 248(C).
    21. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    22. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    23. S.T. Boris Choy & Cathy W.S. Chen & Edward M.H. Lin, 2014. "Bivariate asymmetric GARCH models with heavy tails and dynamic conditional correlations," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1297-1313, July.
    24. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    25. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    26. Asai, Manabu & McAleer, Michael, 2015. "Leverage and feedback effects on multifactor Wishart stochastic volatility for option pricing," Journal of Econometrics, Elsevier, vol. 187(2), pages 436-446.
    27. So, Mike K.P. & Chan, Thomas W.C. & Chu, Amanda M.Y., 2022. "Efficient estimation of high-dimensional dynamic covariance by risk factor mapping: Applications for financial risk management," Journal of Econometrics, Elsevier, vol. 227(1), pages 151-167.
    28. Benjamin Poignard & Manabu Asai, 2022. "High-Dimensional Sparse Multivariate Stochastic Volatility Models," Papers 2201.08584, arXiv.org, revised May 2022.
    29. Trojan, Sebastian, 2014. "Multivariate Stochastic Volatility with Dynamic Cross Leverage," Economics Working Paper Series 1424, University of St. Gallen, School of Economics and Political Science.
    30. Sujay K Mukhoti, "undated". "Dynamic Feedback Effect And Skewness In Non-Stationary Stochastic Volatility Model With Leverage," Working papers 145, Indian Institute of Management Kozhikode.
    31. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  3. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Cited by:

    1. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-953, CIRJE, Faculty of Economics, University of Tokyo.
    2. Shinichiro Shirota & Yashiro Omori & Hedibert Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochasti Volatility Model," Business and Economics Working Papers 224, Unidade de Negocios e Economia, Insper.
    3. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    4. Tsunehiro Ishihara & Yasuhiro Omori, 2017. "Portfolio optimization using dynamic factor and stochastic volatility: evidence on Fat-tailed errors and leverage," The Japanese Economic Review, Japanese Economic Association, vol. 68(1), pages 63-94, March.
    5. Ewa Feder-Sempach & Piotr Szczepocki & Joanna Bogołębska, 2024. "Global uncertainty and potential shelters: gold, bitcoin, and currencies as weak and strong safe havens for main world stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    6. Nakajima, Jouchi & Omori, Yasuhiro, 2012. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3690-3704.
    7. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    8. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2014. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-932, CIRJE, Faculty of Economics, University of Tokyo.
    9. Yuta Kurose & Yasuhiro Omori, 2014. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-941, CIRJE, Faculty of Economics, University of Tokyo.
    10. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    11. Asai, Manabu & McAleer, Michael, 2015. "Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance," Journal of Econometrics, Elsevier, vol. 189(2), pages 251-262.
    12. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-1019, CIRJE, Faculty of Economics, University of Tokyo.
    13. Elchin Suleymanov & Magsud Gubadli & Ulvi Yagubov, 2024. "Test of Volatile Behaviors with the Asymmetric Stochastic Volatility Model: An Implementation on Nasdaq-100," Risks, MDPI, vol. 12(5), pages 1-20, May.
    14. Han Chen & Yijie Fei & Jun Yu, 2026. "Multivariate Stochastic Volatility Model with Block Correlations," Working Papers 202638, University of Macau, Faculty of Business Administration.
    15. Marín Díazaraque, Juan Miguel & Romero, Eva & Veiga, Helena, 2026. "Asymmetric Correlation Propagationin Factor Stochastic Volatility Models," DES - Working Papers. Statistics and Econometrics. WS 50310, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Trojan, Sebastian, 2014. "Multivariate Stochastic Volatility with Dynamic Cross Leverage," Economics Working Paper Series 1424, University of St. Gallen, School of Economics and Political Science.

  4. Tsunehiro Ishihara & Yasuhiro Omori, 2008. ""Markov Switching Asymmetric Stochastic Volatility Model with Application to TOPIX Data -A Permutation Sampler Approach-"(in Japanese)," CIRJE J-Series CIRJE-J-191, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.

  5. Tsunehiro Ishihara & Yasuhiro Omori, 2008. "Markov Switching Asymmetric Stochastic Volatility Model with Application to TOPIX Data -A Permutation Sampler Approach-," CARF J-Series CARF-J-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Cited by:

    1. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.

Articles

  1. Tsunehiro Ishihara & Yasuhiro Omori, 2017. "Portfolio optimization using dynamic factor and stochastic volatility: evidence on Fat-tailed errors and leverage," The Japanese Economic Review, Japanese Economic Association, vol. 68(1), pages 63-94, March.

    Cited by:

    1. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    2. Christian Mücher & Giorgio Calzolari & Roxana Halbleib, 2026. "Sequential estimation of multivariate factor stochastic volatility models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 110(1), pages 41-63, March.
    3. Yuta Yamauchi & Yasuhiro Omori, 2020. "Dynamic factor, leverage and realized covariances in multivariate stochastic volatility," Papers 2011.06909, arXiv.org, revised Sep 2021.
    4. Daichi Hiraki & Siddhartha Chib & Yasuhiro Omori, 2026. "Dynamic Factor Stochastic Volatility-in-Mean VAR for Large Macroeconomic Panels," Papers 2604.04529, arXiv.org.
    5. Ewa Feder-Sempach & Piotr Szczepocki & Joanna Bogołębska, 2024. "Global uncertainty and potential shelters: gold, bitcoin, and currencies as weak and strong safe havens for main world stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-23, December.
    6. Yoshihiro Ohtsuka, 2018. "Large Shocks and the Business Cycle: The Effect of Outlier Adjustments," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 143-178, April.
    7. Tao Sun, 2024. "Bundle Choice Model with Endogenous Regressors: An Application to Soda Tax," Papers 2412.05794, arXiv.org.
    8. 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.

  2. Ishihara, Tsunehiro & Omori, Yasuhiro & Asai, Manabu, 2016. "Matrix exponential stochastic volatility with cross leverage," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 331-350.
    See citations under working paper version above.
  3. Ishihara, Tsunehiro & Watanabe, Toshiaki, 2015. "Econometric Analysis of Business Cycles: A Survey with the Application to the Composite Index in Japan," Economic Review, Hitotsubashi University, vol. 66(2), pages 145-168, April.

    Cited by:

    1. WATANABE, Toshiaki, 2025. "Bayesian Analysis of Business Cycles in Japan by Extending the Markov Switching Model," Discussion paper series HIAS-E-148, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.

  4. Ishihara, Tsunehiro & Omori, Yasuhiro, 2012. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3674-3689.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 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 (3) 2010-01-16 2010-06-11 2013-10-05
  2. NEP-ETS: Econometric Time Series (3) 2010-06-11 2014-05-24 2014-12-03
  3. NEP-ORE: Operations Research (2) 2014-05-24 2014-12-03
  4. NEP-RMG: Risk Management (1) 2014-12-03

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Tsunehiro Ishihara should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.