Gatheral double stochastic volatility model with Skorokhod reflection
Анотація
We investigate the Gatheral model of double mean-reverting stochastic volatility, in which the drift term itself follows a mean-reverting process, and the overall model exhibits mean-reverting behavior. We demonstrate that such processes can attain values arbitrarily close to zero and remain near zero for extended periods, making them practically and statistically indistinguishable from zero. To address this issue, we propose a modified model incorporating Skorokhod reflection, which preserves the model’s flexibility while preventing volatility from approaching zero.
Класифікація
Ідентифікатори
Рецензії (0)
Написати рецензіюРецензій ще немає. Будьте першим!
Схожі роботи
Maximum Likelihood Drift Estimation for the Mixing of Two Fractional Brownian Motions
Схоже за: Stochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
Approximation of multifractional Brownian motion by absolutely continuous processes
Схоже за: Stochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
On a class of minimum contrast estimators for fractional stochastic processes and fields
Схоже за: Stochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
Stochastic differential equations driven by a Wiener process and fractional Brownian motion: Convergence in Besov space with respect to a parameter
Схоже за: Stochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
Two approaches to consistent estimation of parameters of mixed fractional Brownian motion with trend
Схоже за: Stochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
Krylov-Veretennikov expansion for coalescing stochastic flows
Схоже за: Stochastic processes and financial applications · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis