Market information of the fractional stochastic regularity model

The Fractional Stochastic Regularity Model (FSRM) is an extension of Black-Scholes model describing the multifractal nature of prices. It is based on a multifractional process with a random Hurst exponent Ht, driven by a fractional Ornstein-Uhlenbeck (fOU) process. When the regularity parameter Ht is equal to 1/2, the efficient market hypothesis holds, but when Ht≠1/2 past price returns contain some information on a future trend or mean-reversion of the log-price process. In this paper, we investigate some properties of the fOU process and, thanks to information theory and Shannon's entropy, we determine theoretically the serial information of the regularity process Ht of the FSRM, giving some insight into one's ability to forecast future price increments and to build statistical arbitrages with this model.