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Volatility Harvesting: Extracting Return from Randomness

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  • Jan Hendrik Witte

Abstract

Studying Binomial and Gaussian return dynamics in discrete time, we show how excess volatility can be traded to create growth. We test our results on real world data to confirm the observed model phenomena while also highlighting implicit risks.

Suggested Citation

  • Jan Hendrik Witte, 2015. "Volatility Harvesting: Extracting Return from Randomness," Papers 1508.05241, arXiv.org, revised Nov 2015.
    • Handle: RePEc:arx:papers:1508.05241
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    References listed on IDEAS

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    1. Michael A. H. Dempster & Igor V. Evstigneev & Klaus R. Schenk-hoppe, 2007. "Volatility-induced financial growth," Quantitative Finance, Taylor & Francis Journals, vol. 7(2), pages 151-160.
    2. Fernholz, Robert & Shay, Brian, 1982. "Stochastic Portfolio Theory and Stock Market Equilibrium," Journal of Finance, American Finance Association, vol. 37(2), pages 615-624, May.
    3. M. A. H. Dempster & Igor Evstigneev & Klaus Reiner Schenk-Hoppe, 2008. "Financial markets. The joy of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 1-3.
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    Cited by:

    1. Alex Evans, 2020. "Liquidity Provider Returns in Geometric Mean Markets," Papers 2006.08806, arXiv.org, revised Jul 2020.

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