Volatility derivatives are becoming increasingly popular as means for hedging unexpected changes in volatility. Although pricing volatility derivatives demands extreme care in modeling the underlying volatility process, not much attention has been devoted to the complete specification of the autonomous process that volatility follows in continuous time. Despite the fact that jumps are widely co...

This paper investigates the conditional correlations and volatility spillovers between the dollar exchange rate return, gold coin return and crude oil return to stock index return. Monthly returns in the 144 observations (2005 - 2017) are analyzed by constant conditional correlation, dynamic conditional correlation, VARMA-GARCH and VARMA-AGARCH models. So this paper presents interdependences in...

Outline Introduction Semi-parametric dynamic copula Motivation Local likelihood estimation Variance of the estimator Bias of the estimator Bandwidth selection Estimation of joint likelihood Modeling of marginal distributions Simulations and applications Simulations Empirical example Conclusions Problems and Solutions Problems Modeling dependence is critical for financial time series Model volat...

This paper develops a novel approach to modeling and forecasting realized volatility (RV) measures based on copula functions. Copula-based time series models can capture relevant characteristics of volatility such as nonlinear dynamics and long-memory type behavior in a flexible yet parsimonious way. In an empirical application to daily volatility for S&P500 index futures, we find that the copu...

There is much literature that deals with modeling and forecasting asset return volatility. However, much of this research does not attempt to explain variations in the level of volatility. Movements in volatility are often linked to trading volume or frequency, as a reflection of underlying information flow. This paper considers whether the state of an open limit order book influences volatilit...

We consider a simple uncertain-volatility model for the asset price underlying a given option market. The asset price volatility is assumed to follow a discrete (actually finite) Markov chain σ, which changes value on some fixed future times. The volatility chain is independent of the Brownian motion governing the future evolution of the asset. Modeling the volatility evolution in this way is e...