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Spectral risk measure of holding stocks in the long run

Author

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  • Zsolt Bihary

    (Corvinus University of Budapest, Corvinus Business School, Department of Finance)

  • Peter Csoka

    ("Momentum" Game Theory Research Group, Centre for Economic and Regional Studies, Hungarian Academy of Sciences and Corvinus University of Budapest, Corvinus Business School, Department of Finance)

  • David Zoltan Szabo

    (School of Mathematics, University of Manchester)

Abstract

We investigate how the spectral risk measure associated with holding stocks rather than a risk-free deposit, depends on the holding period. Previous papers have shown that within a limited class of spectral risk measures, and when the stock price follows specific processes, spectral risk becomes negative at long periods. We generalize this result for arbitrary exponential Lévy processes. We also prove the same behavior for all spectral risk measures (including the important special case of Expected Shortfall) when the stock price grows realistically fast and when it follows a Geometric Brownian Motion or a Finite Moment Log Stable process. This result would suggest that holding stocks for long periods has a vanishing risk. However, using realistic models, we find numerically that the risk increases for a few decades and reaches zero at around 100 years. Therefore, we conclude that holding stocks is risky for all practically relevant periods.

Suggested Citation

  • Zsolt Bihary & Peter Csoka & David Zoltan Szabo, 2018. "Spectral risk measure of holding stocks in the long run," CERS-IE WORKING PAPERS 1812, Institute of Economics, Centre for Economic and Regional Studies.
  • Handle: RePEc:has:discpr:1812
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    as
    1. repec:bla:jfinan:v:58:y:2003:i:2:p:753-778 is not listed on IDEAS
    2. Aleksander Janicki & Aleksander Weron, 1994. "Simulation and Chaotic Behavior of Alpha-stable Stochastic Processes," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook9401, December.
    3. Labreuche, Christophe & Grabisch, Michel, 2018. "Using multiple reference levels in Multi-Criteria Decision aid: The Generalized-Additive Independence model and the Choquet integral approaches," European Journal of Operational Research, Elsevier, vol. 267(2), pages 598-611.
    4. Peter Carr & Liuren Wu, 2003. "The Finite Moment Log Stable Process and Option Pricing," Journal of Finance, American Finance Association, vol. 58(2), pages 753-777, April.
    5. Ning Cai & S. G. Kou, 2011. "Option Pricing Under a Mixed-Exponential Jump Diffusion Model," Management Science, INFORMS, vol. 57(11), pages 2067-2081, November.
    6. Fu, Jun & Yang, Hailiang, 2012. "Equilibruim approach of asset pricing under Lévy process," European Journal of Operational Research, Elsevier, vol. 223(3), pages 701-708.
    7. Steve Ross, 2015. "The Recovery Theorem," Journal of Finance, American Finance Association, vol. 70(2), pages 615-648, April.
    8. Michel Grabisch & Christophe Labreuche, 2010. "A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid," Annals of Operations Research, Springer, vol. 175(1), pages 247-286, March.
    9. Ľuboš Pástor & Robert F. Stambaugh, 2012. "Are Stocks Really Less Volatile in the Long Run?," Journal of Finance, American Finance Association, vol. 67(2), pages 431-478, April.
    10. Wang, Shaun, 1996. "Premium Calculation by Transforming the Layer Premium Density," ASTIN Bulletin, Cambridge University Press, vol. 26(1), pages 71-92, May.
    11. Carlo Acerbi & Giacomo Scandolo, 2008. "Liquidity risk theory and coherent measures of risk," Quantitative Finance, Taylor & Francis Journals, vol. 8(7), pages 681-692.
    12. Benoit Mandelbrot, 1963. "New Methods in Statistical Economics," Journal of Political Economy, University of Chicago Press, vol. 71(5), pages 421-421.
    13. Csoka, Peter & Herings, P. Jean-Jacques & Koczy, Laszlo A., 2007. "Coherent measures of risk from a general equilibrium perspective," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2517-2534, August.
    14. Miller, Naomi & Ruszczynski, Andrzej, 2008. "Risk-adjusted probability measures in portfolio optimization with coherent measures of risk," European Journal of Operational Research, Elsevier, vol. 191(1), pages 193-206, November.
    15. Gianluca Fusai & Ioannis Kyriakou, 2016. "General Optimized Lower and Upper Bounds for Discrete and Continuous Arithmetic Asian Options," Mathematics of Operations Research, INFORMS, vol. 41(2), pages 531-559, May.
    16. Riedel, Frank, 2004. "Dynamic coherent risk measures," Stochastic Processes and their Applications, Elsevier, vol. 112(2), pages 185-200, August.
    17. Acerbi, Carlo, 2002. "Spectral measures of risk: A coherent representation of subjective risk aversion," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1505-1518, July.
    18. Hung Nguyen & Uyen Pham & Hien Tran, 2012. "On some claims related to Choquet integral risk measures," Annals of Operations Research, Springer, vol. 195(1), pages 5-31, May.
    19. Masahiko Egami & Tadao Oryu, 2015. "An Excursion-Theoretic Approach to Regulator’s Bank Reorganization Problem," Operations Research, INFORMS, vol. 63(3), pages 527-539, June.
    20. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    21. Carlo Acerbi & Dirk Tasche, 2002. "Expected Shortfall: A Natural Coherent Alternative to Value at Risk," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(2), pages 379-388, July.
    22. Ahmed, Shabbir & Cakmak, Ulas & Shapiro, Alexander, 2007. "Coherent risk measures in inventory problems," European Journal of Operational Research, Elsevier, vol. 182(1), pages 226-238, October.
    23. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    24. Philpott, A.B. & de Matos, V.L., 2012. "Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion," European Journal of Operational Research, Elsevier, vol. 218(2), pages 470-483.
    25. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath & Hyejin Ku, 2007. "Coherent multiperiod risk adjusted values and Bellman’s principle," Annals of Operations Research, Springer, vol. 152(1), pages 5-22, July.
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    1. Csóka, Péter & Bihary, Zsolt & Kondor, Gábor, 2018. "A részvénytartás spektrális kockázata hosszú távon [On the spectral measure of risk in holding stocks in the long run]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 687-700.
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    3. Josa-Fombellida, Ricardo & López-Casado, Paula, 2023. "A defined benefit pension plan game with Brownian and Poisson jumps uncertainty," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1294-1311.

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    More about this item

    Keywords

    Coherent Risk Measures; Spectral Risk Measures; Lévy processes; Finite Moment Log Stable Model; Time Diversification;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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