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Jumps and Dynamic Asset Allocation

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  • Wu, Liuren

Abstract

This paper analyzes the optimal dynamic asset allocation problem in economies with infrequent events and where the investment opportunities are stochastic and predictable. Analytical approximations are obtained, with which a thorough comparative study is performed on the impacts of jumps upon the dynamic decision. The model is then calibrated to the U.S. equity market. The comparative analysis and the calibration exercise both show that jump risk not only makes the investor's allocation more conservative overall but also makes her dynamic portfolio rebalancing less dramatic over time. Copyright 2003 by Kluwer Academic Publishers

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  • Wu, Liuren, 2003. "Jumps and Dynamic Asset Allocation," Review of Quantitative Finance and Accounting, Springer, vol. 20(3), pages 207-243, May.
    • Handle: RePEc:kap:rqfnac:v:20:y:2003:i:3:p:207-43
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    Cited by:

    1. Jin-Huei Yeh & Jying-Nan Wang & Chung-Ming Kuan, 2014. "A noise-robust estimator of volatility based on interquantile ranges," Review of Quantitative Finance and Accounting, Springer, vol. 43(4), pages 751-779, November.
    2. Muck, Matthias, 2010. "Trading strategies with partial access to the derivatives market," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1288-1298, June.
    3. Asgharian, Hossein & Nossman, Marcus, 2011. "Risk contagion among international stock markets," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 22-38, February.
    4. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    5. Martin Kipp & Christian Koziol, 2022. "Tail risk management and the skewness premium," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 534-546, October.
    6. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2020. "Oil shocks and volatility jumps," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 247-272, January.
    7. Branger, Nicole & Kraft, Holger & Meinerding, Christoph, 2014. "Partial information about contagion risk, self-exciting processes and portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 18-36.
    8. Branger, Nicole & Muck, Matthias & Seifried, Frank Thomas & Weisheit, Stefan, 2017. "Optimal portfolios when variances and covariances can jump," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 59-89.
    9. Anna Battauz & Alessandro Sbuelz, 2018. "Non†myopic portfolio choice with unpredictable returns: The jump†to†default case," European Financial Management, European Financial Management Association, vol. 24(2), pages 192-208, March.
    10. Josa-Fombellida, Ricardo & Rincón-Zapatero, Juan Pablo, 2012. "Stochastic pension funding when the benefit and the risky asset follow jump diffusion processes," European Journal of Operational Research, Elsevier, vol. 220(2), pages 404-413.
    11. He, Lin & Liang, Zongxia, 2013. "Optimal dynamic asset allocation strategy for ELA scheme of DC pension plan during the distribution phase," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 404-410.
    12. Liu, Qingfu & Tu, Anthony H., 2012. "Jump spillovers in energy futures markets: Implications for diversification benefits," Energy Economics, Elsevier, vol. 34(5), pages 1447-1464.
    13. In Kim & In-Seok Baek & Jaesun Noh & Sol Kim, 2007. "The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 29(1), pages 69-110, July.
    14. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    15. 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.
    16. Chia-Chi Lu & Weifeng Hung & Jyh-Jian Sheu & Pai-Ta Shih, 2011. "Investment with network externality under uncertainty," Review of Quantitative Finance and Accounting, Springer, vol. 36(4), pages 555-564, May.
    17. Hui-Ju Tsai & Yangru Wu, 2015. "Optimal portfolio choice with asset return predictability and nontradable labor income," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 215-249, July.
    18. Rytchkov, Oleg, 2016. "Time-Varying Margin Requirements and Optimal Portfolio Choice," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(2), pages 655-683, April.
    19. Mu, Congming & Yan, Jingzhou & Liang, Zhian, 2021. "Optimal risk taking under high-water mark contract with jump risk," Finance Research Letters, Elsevier, vol. 38(C).
    20. Kshatriya, Saranya & Prasanna, Krishna, 2021. "Jump Interdependencies: Stochastic linkages among international stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    21. Chen, Ke & Vitiello, Luiz & Hyde, Stuart & Poon, Ser-Huang, 2018. "The reality of stock market jumps diversification," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 171-188.
    22. Jin-Ray Lu & Chih-Ming Chan, 2014. "Optimal portfolio choice of gold assets in the differential market and differential game structures," Review of Quantitative Finance and Accounting, Springer, vol. 42(2), pages 309-325, February.
    23. Ngwira, Bernard & Gerrard, Russell, 2007. "Stochastic pension fund control in the presence of Poisson jumps," Insurance: Mathematics and Economics, Elsevier, vol. 40(2), pages 283-292, March.

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