Arbitrage in Fractal Modulated Markets When the Volatility is Stochastic
Erhan Bayraktar, H. Vincent Poor

TL;DR
This paper develops an arbitrage strategy for a modified Black-Scholes model driven by fractional Brownian motion with stochastic volatility, extending previous models to account for heavy tails and long-range dependence in stock returns.
Contribution
It introduces a novel arbitrage approach for stochastic volatility models driven by fractional Brownian motion or its time change, addressing the non-semimartingale nature of fractional Brownian motion.
Findings
Arbitrage strategy applicable to fractional Brownian motion driven models.
Shows that integrals with zero quadratic variation can serve as integrators.
Discusses the suitability of fractional Brownian motion for modeling stock returns.
Abstract
In this paper an arbitrage strategy is constructed for the modified Black-Scholes model driven by fractional Brownian motion or by a time changed fractional Brownian motion, when the volatility is stochastic. This latter property allows the heavy tailedness of the log returns of the stock prices to be also accounted for in addition to the long range dependence introduced by the fractional Brownian motion. Work has been done previously on this problem for the case with constant `volatility' and without a time change; here these results are extended to the case of stochastic volatility models when the modulator is fractional Brownian motion or a time change of it. (Volatility in fractional Black-Scholes models does not carry the same meaning as in the classic Black-Scholes framework, which is made clear in the text.) Since fractional Brownian motion is not a semi-martingale, the…
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Taxonomy
TopicsStochastic processes and financial applications · Complex Systems and Time Series Analysis · Financial Risk and Volatility Modeling
