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Realistic Statistical Modelling of Financial Data

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  • Tina Hviid Rydberg

Abstract

The aim of this paper is to present some of the stylized features of financial data which have received a lot of attention both from practitioners and those with more theoretical backgrounds. Some of the models resulting from these efforts are reviewed and discussed. To facilitate the discussion two data sets are used: one of these contains all US trades in IBM stocks in 1995 at NYSE.

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  • Tina Hviid Rydberg, 2000. "Realistic Statistical Modelling of Financial Data," International Statistical Review, International Statistical Institute, vol. 68(3), pages 233-258, December.
    • Handle: RePEc:bla:istatr:v:68:y:2000:i:3:p:233-258
    DOI: 10.1111/j.1751-5823.2000.tb00329.x
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    Cited by:

    1. Pan, Jiazhu & Wang, Hui & Tong, Howell, 2008. "Estimation and tests for power-transformed and threshold GARCH models," Journal of Econometrics, Elsevier, vol. 142(1), pages 352-378, January.
    2. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & AL-Dhurafi, Nasr Ahmed, 2020. "The power-law distribution for the income of poor households," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    3. Li, Dong & Tao, Yuxin & Yang, Yaxing & Zhang, Rongmao, 2023. "Maximum likelihood estimation for α-stable double autoregressive models," Journal of Econometrics, Elsevier, vol. 236(1).
    4. Kovačić, Zlatko, 2007. "Forecasting volatility: Evidence from the Macedonian stock exchange," MPRA Paper 5319, University Library of Munich, Germany.
    5. Lesedi Mabitsela & Eben Maré & Rodwell Kufakunesu, 2015. "Quantification of VaR: A Note on VaR Valuation in the South African Equity Market," JRFM, MDPI, vol. 8(1), pages 1-24, February.
    6. Griffin, J.E. & Steel, M.F.J., 2006. "Inference with non-Gaussian Ornstein-Uhlenbeck processes for stochastic volatility," Journal of Econometrics, Elsevier, vol. 134(2), pages 605-644, October.
    7. Katahira, Kei & Chen, Yu & Akiyama, Eizo, 2021. "Self-organized Speculation Game for the spontaneous emergence of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    8. Ekong, Christopher N. & Onye, Kenneth U., 2017. "Application of Garch Models to Estimate and Predict Financial Volatility of Daily Stock Returns in Nigeria," MPRA Paper 88309, University Library of Munich, Germany.
    9. Jun Lu & Shao Yi, 2022. "Autoencoding Conditional GAN for Portfolio Allocation Diversification," Applied Economics and Finance, Redfame publishing, vol. 9(3), pages 55-68, August.
    10. Lillestøl, Jostein, 2007. "Some new bivariate IG and NIG-distributions for modelling covariate nancial returns," Discussion Papers 2007/1, Norwegian School of Economics, Department of Business and Management Science.
    11. Støve, Bård & Tjøstheim, Dag & Hufthammer, Karl Ove, 2010. "Measuring Financial Contagion by Local Gaussian Correlation," Discussion Papers 2010/12, Norwegian School of Economics, Department of Business and Management Science.
    12. Chronis, George A., 2016. "Modelling the extreme variability of the US Consumer Price Index inflation with a stable non-symmetric distribution," Economic Modelling, Elsevier, vol. 59(C), pages 271-277.
    13. Jun Lu & Shao Yi, 2022. "Autoencoding Conditional GAN for Portfolio Allocation Diversification," Papers 2207.05701, arXiv.org.
    14. Jin, Hao & Tian, Zheng & Qin, Ruibing, 2009. "Subsampling tests for the mean change point with heavy-tailed innovations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2157-2166.
    15. Vinicius Ratton Brandi, 2020. "Short-Term Predictability of Stock Market Indexes following Large Drawdowns and Drawups," Working Papers Series 529, Central Bank of Brazil, Research Department.
    16. BenSaïda, Ahmed & Slim, Skander, 2016. "Highly flexible distributions to fit multiple frequency financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 203-213.
    17. Ivivi Joseph Mwaniki, 2019. "Modeling heteroscedastic, skewed and leptokurtic returns in discrete time," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(5), pages 1-1.
    18. Kei Katahira & Yu Chen, 2019. "Heterogeneous wealth distribution, round-trip trading and the emergence of volatility clustering in Speculation Game," Papers 1909.03185, arXiv.org.
    19. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    20. Katahira, Kei & Chen, Yu & Hashimoto, Gaku & Okuda, Hiroshi, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 503-518.
    21. Norbert Henze & María Dolores Jiménez-Gamero, 2019. "A new class of tests for multinormality with i.i.d. and garch data based on the empirical moment generating function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 499-521, June.
    22. Støve, Bård & Tjøstheim, Dag & Hufthammer, Karl Ove, 2014. "Using local Gaussian correlation in a nonlinear re-examination of financial contagion," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 62-82.
    23. Homm, Ulrich & Pigorsch, Christian, 2012. "Beyond the Sharpe ratio: An application of the Aumann–Serrano index to performance measurement," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2274-2284.
    24. Peter Karlsson, 2011. "The Incompleteness Problem of the APT Model," Computational Economics, Springer;Society for Computational Economics, vol. 38(2), pages 129-151, August.

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