IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v43y2014icp9-20.html
   My bibliography  Save this article

A two-regime threshold model with conditional skewed Student t distributions for stock returns

Author

Listed:
  • Massacci, Daniele

Abstract

This paper proposes a two-regime threshold model for the conditional distribution of stock returns in which returns follow a distinct skewed Student t distribution within each regime: the model allows capturing time variation in the conditional distribution of returns, as well as higher order moments. An application of the model to daily U.S. stock returns illustrates the advantages of the proposed model in comparison to alternative specifications: the model performs well in terms of in-sample fit; it more accurately estimates the conditional volatility; and it produces useful risk assessment as measured by the term structure of value at risk.

Suggested Citation

  • Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    • Handle: RePEc:eee:ecmode:v:43:y:2014:i:c:p:9-20
    DOI: 10.1016/j.econmod.2014.07.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999314002880
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2014.07.032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Gabriel Perez‐Quiros & Allan Timmermann, 2000. "Firm Size and Cyclical Variations in Stock Returns," Journal of Finance, American Finance Association, vol. 55(3), pages 1229-1262, June.
    3. 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.
    4. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, September.
    5. Perez-Quiros, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 259-306, July.
    6. Bauwens, Luc & Laurent, Sebastien, 2005. "A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 346-354, July.
    7. Massimo Guidolin & Allan Timmermann, 2006. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 1-22, January.
    8. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    9. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(4), pages 465-487, December.
    10. Li, Ting & Zhang, Weiguo & Xu, Weijun, 2013. "Fuzzy possibilistic portfolio selection model with VaR constraint and risk-free investment," Economic Modelling, Elsevier, vol. 31(C), pages 12-17.
    11. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    12. Francq, Christian & Zakoian, Jean-Michel, 2013. "Inference in non stationary asymmetric garch models," MPRA Paper 44901, University Library of Munich, Germany.
    13. Peter F. Christoffersen & Francis X. Diebold, 2000. "How Relevant is Volatility Forecasting for Financial Risk Management?," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 12-22, February.
    14. Massacci, Daniele, 2013. "A switching model with flexible threshold variable: With an application to nonlinear dynamics in stock returns," Economics Letters, Elsevier, vol. 119(2), pages 199-203.
    15. Hansen Bruce E., 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(1), pages 1-16, April.
    16. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    17. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    18. Francis X. Diebold (ed.), 2012. "Financial Risk Measurement and Management," Books, Edward Elgar Publishing, number 14102.
    19. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    20. Shephard, Neil (ed.), 2005. "Stochastic Volatility: Selected Readings," OUP Catalogue, Oxford University Press, number 9780199257201.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    4. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    5. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
    6. 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.
    7. C. James Hueng & Ruey Yau, 2006. "Investor preferences and portfolio selection: is diversification an appropriate strategy?," Quantitative Finance, Taylor & Francis Journals, vol. 6(3), pages 255-271.
    8. Yang (Greg) Hou & Mark Holmes, 2020. "Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 240-265, May.
    9. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
    10. Venetis, Ioannis A. & Peel, David, 2005. "Non-linearity in stock index returns: the volatility and serial correlation relationship," Economic Modelling, Elsevier, vol. 22(1), pages 1-19, January.
    11. Zhu, Ke & Li, Wai Keung, 2013. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52344, University Library of Munich, Germany.
    12. Hashmi, Aamir R. & Tay, Anthony S., 2007. "Global regional sources of risk in equity markets: Evidence from factor models with time-varying conditional skewness," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 430-453, April.
    13. Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021. "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(1), pages 65-91, February.
    14. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
    15. Andrew Ang & Allan Timmermann, 2012. "Regime Changes and Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 313-337, October.
    16. Vijverberg, Chu-Ping C. & Vijverberg, Wim P.M. & Taşpınar, Süleyman, 2016. "Linking Tukey’s legacy to financial risk measurement," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 595-615.
    17. Hou, Yang & Holmes, Mark, 2017. "On the effects of static and autoregressive conditional higher order moments on dynamic optimal hedging," MPRA Paper 82000, University Library of Munich, Germany.
    18. Trung H. Le, 2024. "Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 402-414, March.
    19. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    20. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:43:y:2014:i:c:p:9-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    Please note that corrections may 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.