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Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy

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  • Claudiu Vinte
  • Marcel Ausloos

Abstract

Selecting stock portfolios and assessing their relative volatility risk compared to the market as a whole, market indices, or other portfolios is of great importance to professional fund managers and individual investors alike. Our research uses the cross-sectional intrinsic entropy (CSIE) model to estimate the cross-sectional volatility of the stock groups that can be considered together as portfolio constituents. In our study, we benchmark portfolio volatility risks against the volatility of the entire market provided by the CSIE and the volatility of market indices computed using longitudinal data. This article introduces CSIE-based betas to characterise the relative volatility risk of the portfolio against market indices and the market as a whole. We empirically prove that, through CSIE-based betas, multiple sets of symbols that outperform the market indices in terms of rate of return while maintaining the same level of risk or even lower than the one exhibited by the market index can be discovered, for any given time interval. These sets of symbols can be used as constituent stock portfolios and, in connection with the perspective provided by the CSIE volatility estimates, to hierarchically assess their relative volatility risk within the broader context of the overall volatility of the stock market.

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  • Claudiu Vinte & Marcel Ausloos, 2023. "Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy," Papers 2303.09330, arXiv.org.
  • Handle: RePEc:arx:papers:2303.09330
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    1. Fan, Jianqing & Han, Fang & Liu, Han & Vickers, Byron, 2016. "Robust inference of risks of large portfolios," Journal of Econometrics, Elsevier, vol. 194(2), pages 298-308.
    2. Gurjeet Dhesi & Marcel Ausloos, 2016. "Modelling and Measuring the Irrational behaviour of Agents in Financial Markets: Discovering the Psychological Soliton," Papers 1601.01553, arXiv.org.
    3. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    4. González-Urteaga, Ana & Rubio, Gonzalo, 2016. "The cross-sectional variation of volatility risk premia," Journal of Financial Economics, Elsevier, vol. 119(2), pages 353-370.
    5. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    6. Jianqing Fan & Donggyu Kim, 2018. "Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1268-1283, July.
    7. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    8. Atanu Saha & Burton G. Malkiel & Alex Rinaudo, 2019. "Has the VIX index been manipulated?," Journal of Asset Management, Palgrave Macmillan, vol. 20(1), pages 1-14, February.
    9. Moawia Alghalith, 2016. "Estimating the Stock/Portfolio Volatility and the Volatility of Volatility: A New Simple Method," Econometric Reviews, Taylor & Francis Journals, vol. 35(2), pages 257-262, February.
    10. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    11. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2007. "Entropy and Uncertainty Analysis in Financial Markets," Papers 0709.0668, arXiv.org.
    12. Ausloos, Marcel, 2016. "Modelling and measuring the irrational behaviour of agents in financial markets: Discovering the psychological solitonAuthor-Name: Dhesi, Gurjeet," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 119-125.
    13. Fama, Eugene F & French, Kenneth R, 1995. "Size and Book-to-Market Factors in Earnings and Returns," Journal of Finance, American Finance Association, vol. 50(1), pages 131-155, March.
    14. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    15. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    16. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    17. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    18. Ausloos, M., 2000. "Gas-kinetic theory and Boltzmann equation of share price within an equilibrium market hypothesis and ad hoc strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 284(1), pages 385-392.
    19. Peter Carr & Liuren Wu, 2009. "Variance Risk Premiums," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1311-1341, March.
    20. Barinov, Alexander, 2012. "Aggregate volatility risk: Explaining the small growth anomaly and the new issues puzzle," Journal of Corporate Finance, Elsevier, vol. 18(4), pages 763-781.
    21. Alan Moreira & Tyler Muir, 2017. "Volatility-Managed Portfolios," Journal of Finance, American Finance Association, vol. 72(4), pages 1611-1644, August.
    22. Fan, Jianqing & Fan, Yingying & Lv, Jinchi, 2008. "High dimensional covariance matrix estimation using a factor model," Journal of Econometrics, Elsevier, vol. 147(1), pages 186-197, November.
    23. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
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