Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model

A Multifractional Process with Random Exponent (MPRE) is used to model the dynamics of log-prices in a financial market. Under this assumption, we show that the Hurst-Holder exponent of the MPRE follows the fractional Ornstein-Uhlenbeck process which in the Fractional Stochastic Volatility Model of Comte and Renault (1998) describes the dynamics of the log-volatility. We provide evidence that several biases of the estimation procedures can generate artificial rough volatility in surrogated as well as real financial data.

Automated summary

A Multifractional Process with Random Exponent (MPRE) is used to simulate the dynamics of log-prices in a financial market. It is shown that the Hurst-Holder exponent of the MPRE follows the fractional Ornstein-Uhlenbeck process, which describes the dynamics of the log-volatility in the Fractional Stochastic Volatility Model. Evidence is provided to demonstrate that estimation biases can generate artificial rough volatility in both surrogated and real financial data.