market, volatility and jump risks, and observation error of time changes. To operationalize the models, we use volume …

Brownian motion. -- asymptotic uniformity ; local limit theorem ; volatility …

We develop a new efficient and analytically tractable method for estimation of parametric volatility models that is …-day data into the Realized Laplace Transform of volatility, which is a model-free and jump-robust estimate of daily integrated … empirical Laplace transform of the unobservable volatility. The estimation then is done by matching moments of the integrated …

This article studies the impact of long memory on volatility modelling and option pricing. We propose a general … discrete-time pricing framework based on affine multi-component volatility models that admit ARCH(ccc) representations. This … the parameter estimation process, the inclusion of long-memory dynamics in volatility is beneficial for improving the out …

volatility's hidden state. Stochastic volatility is the unobserved state in a hidden Markov model (HMM), and can be tracked using … density on volatility. Our analysis relies on a specification of the martingale change of measure, which we will refer to as … separability. This specification has a multiplicative component that behaves like a risk premium on volatility-uncertainty in the …