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Ergodic aspects of trading with threshold strategies

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  • Attila Lovas
  • Mikl'os R'asonyi

Abstract

To profit from price oscillations, investors frequently use threshold-type strategies where changes in the portfolio position are triggered by some indicators reaching prescribed levels. In this paper, we investigate threshold-type strategies in the context of ergodic control. We make the first steps towards their optimization by proving the ergodic properties of related functionals. Assuming Markovian price increments satisfying a minorization condition and (one-sided) boundedness we show, in particular, that for given thresholds, the distribution of the gains converges in the long run. We also extend recent results on the stability of overshoots of random walks from the i.i.d.\ increment case to Markovian increments, under suitable conditions.

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  • Attila Lovas & Mikl'os R'asonyi, 2021. "Ergodic aspects of trading with threshold strategies," Papers 2111.14708, arXiv.org, revised Jul 2022.
    • Handle: RePEc:arx:papers:2111.14708
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    1. Fabienne Comte & Eric Renault, 1998. "Long memory in continuous‐time stochastic volatility models," Mathematical Finance, Wiley Blackwell, vol. 8(4), pages 291-323, October.
    2. Jim Gatheral & Thibault Jaisson & Mathieu Rosenbaum, 2018. "Volatility is rough," Quantitative Finance, Taylor & Francis Journals, vol. 18(6), pages 933-949, June.
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    Cited by:

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