Semiparametric Asymmetric Stochastic Volatility∗

Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture

In this paper we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. Its novelty is in modeling the joint, conditional, return-volatility, distribution with a infinite mixture of bivariate Normal distributions with mean zero ...

Modelling Stochastic Volatility in Asset Returns Using Fractionally Integrated Semiparametric Techniques

Modeling Stock Return Volatility Using Symmetric and Asymmetric Nonlinear State Space Models: Case of Tehran Stock Market

Volatility is a measure of uncertainty that plays a central role in financial theory, risk management, and pricing authority. Turbulence is the conditional variance of changes in asset prices that is not directly observable and is considered a hidden variable that is indirectly calculated using some approximations. To do this, two general approaches are presented in the literature of financial ...

Semiparametric estimation of volatility functions of diffusion processes from discretely observed data

This paper provides a semiparametric model to estimate processes of the volatility defined as the squared diffusion coefficient of a stochastic differential equation. Without assuming any functional form of the volatility function, we estimate the volatility process by filtering. We prove the consistency of the model in the sense that estimated processes converge to the true ones as the number ...

Econometric Analysis of Jump-Driven Stochastic Volatility Models

This paper introduces and studies the econometric properties of a general new class of models, which I refer to as jump-driven stochastic volatility models, in which the volatility is a moving average of past jumps. I focus attention on two particular semiparametric classes of jump-driven stochastic volatility models. In the first the price has a continuous component with time-varying volatilit...