Markov-switching Heston's stochastic volatility model. Under this framework, the expected return and the long-term mean of … evidence that the Markov-switching Heston's stochastic volatility model performs well in capturing major events affecting price … volatility model. …

Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and … the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper …, we extend the stochastic volatility (SV) model for application with such intraday high-frequency data and develop an …

This paper proposes the sample path generation method for the stochastic volatility version of the CGMY process. We …

The paper builds a Variance-Gamma (VG) model with five parameters: location (μ), symmetry (δ), volatility (σ), shape (α … five-parameter VG model is a stochastic volatility model with a Γ(α,θ) Ornstein-Uhlenbeck type process; the associated Lévy …

one-month variance swap rate, i.e., the CBOE Volatility Index (VIX) accurately. Our research suggests that one should use …

This paper studies multiscale stochastic volatility models of financial asset returns. It specifies two components in … the log-volatility process and allows for leverage/asymmetric effects from both components while return innovation terms … dependence in return volatility, which is often absent in applications of stochastic volatility models which incorporate leverage …

This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets … (Brent oil and WTI oil) for the period 2011-2021. The main objective is to make step ahead volatility predictions for the … important for market participants, implying predictability. The paper estimates multifactor stochastic volatility models for …

use of computational methods and techniques for modelling financial asset prices, returns, and volatility, and on the use …