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Stylized facts of financial time series and hidden semi-Markov models

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  • Bulla, Jan
  • Bulla, Ingo

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Bibliographic Info

Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 51 (2006)
Issue (Month): 4 (December)
Pages: 2192-2209

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Handle: RePEc:eee:csdana:v:51:y:2006:i:4:p:2192-2209

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Web page: http://www.elsevier.com/locate/csda

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References

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  1. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5&6), pages 523-554.
  2. Turner, C.M. & Startz, R. & Nelson, C.R., 1989. "The Markov Model Of Heteroskedasticity, Risk And Learning In The Stock Market," Discussion Papers in Economics at the University of Washington 89-01, Department of Economics at the University of Washington.
  3. Christopher M. Turner & Richard Startz & Charles R. Nelson, 1989. "A Markov Model of Heteroskedasticity, Risk, and Learning in the Stock Market," NBER Working Papers 2818, National Bureau of Economic Research, Inc.
  4. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, October.
  5. G. D. Gettinby & C. D. Sinclair & D. M. Power & R. A. Brown, 2004. "An Analysis of the Distribution of Extreme Share Returns in the UK from 1975 to 2000," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5-6), pages 607-646.
  6. Stephen G. Cecchetti & Pok-sang Lam & Nelson C. Mark, 1988. "Mean Reversion in Equilibrium Asset Prices," NBER Working Papers 2762, National Bureau of Economic Research, Inc.
  7. Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004. "Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements," Tinbergen Institute Discussion Papers 04-016/4, Tinbergen Institute.
  8. Praetz, Peter D, 1972. "The Distribution of Share Price Changes," The Journal of Business, University of Chicago Press, vol. 45(1), pages 49-55, January.
  9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  10. Rydén, Tobias & Teräsvirta, Timo & Åsbrink, Stefan, 1996. "Stylized Facts of Daily Return Series and the Hidden Markov Model," Working Paper Series in Economics and Finance 117, Stockholm School of Economics.
  11. C. W. J. GRANGER & Zhuanxin DING, 1995. "Some Properties of Absolute Return: An Alternative Measure of Risk," Annales d'Economie et de Statistique, ENSAE, issue 40, pages 67-91.
  12. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," The Journal of Business, University of Chicago Press, vol. 47(2), pages 244-80, April.
  13. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
  14. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  15. Richard D. F. Harris & C. Coskun Küçüközmen, 2001. "The Empirical Distribution of UK and US Stock Returns," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(5-6), pages 715-740.
  16. Jun Yu, 2002. "Forecasting volatility in the New Zealand stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(3), pages 193-202.
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Cited by:
  1. Elliott, Robert & Limnios, Nikolaos & Swishchuk, Anatoliy, 2013. "Filtering hidden semi-Markov chains," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2007-2014.
  2. Giampiero Gallo & Edoardo Otranto, 2007. "Volatility Spillovers, Interdependence and Comovements: A Markov Switching Approach," Econometrics Working Papers Archive wp2007_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  3. Bulla, Jan, 2009. "Hidden Markov models with t components. Increased persistence and other aspects," MPRA Paper 21830, University Library of Munich, Germany.
  4. Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
  5. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1682-1700, August.
  6. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.

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