UC Irvine

In recent years, there has been growing interest in modeling volatility as a stochastic process driven by a non-Markovian process, due to empirical evidence showing that the autocorrelation function of volatility decays as a power function. This paper investigates the use of a time-scaled fractional Ornstein-Uhlenbeck process to model volatility and applies this model to derive an optimal delta hedging strategy. By incorporating non-Markovian processes into our model, we aim to provide insights into the behavior of volatility in financial markets and explore potential benefits for option pricing and risk management strategies.