This paper proposes a range-based dynamic conditional correlation (DCC) model combined by the return-based DCC model and the conditional autoregressive range (CARR) model. The substantial gain in efficiency of volatility estimation can boost the accuracy for estimating time-varying covariances....

This paper considers a simple Continuous Beliefs System (CBS) toinvestigate the effects on price dynamics of several behavioralassumptions: (i) herd behaviour; (ii) a-synchronous updating ofbeliefs; and (iii) heterogeneity in time horizons (memory) amongagents. The recently introduced concept of...

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR has been extensively used to measure systematic risk exposure in developed markets like of the US, Europe and Asia. This paper analyzes the accuracy of VaR measure for Pakistan's emerging...

We consider the problems of derivative pricing and inference when the stochastic discount factor has an exponential-affine form and the geometric return of the underlying asset has a dynamics characterized by a mixture of conditionally Normal processes. We consider both the static case in which...

This paper introduces the class of volatility modulated Lévy-driven Volterra (VMLV) processes and their important subclass of Lévy semistationary (LSS) processes as a new framework for modelling energy spot prices. The main modelling idea consists of four principles: First, deseasonalised spot...

The estimation of multivariate GARCH time series models is a difficult task mainly due to the excessive parameterization exhibited by the problem, usually referred to as the "curse of dimensionality." For the VEC family, the number of parameters involved in the model grows as a polynomial of...

We propose different schemes for option hedging when asset returns are modeled using a general class of GARCH models. More specifically, we implement local risk minimization and a minimum variance hedge approximation based on an extended Girsanov principle that generalizes Duan's (1995) delta...

This paper aims to describe bias estimates when non-stationary variance is not detected. We first present a theoretical multivariate GARCH model with structural changes in variance. Then we describe the non-stationary variance and Volatility Causality in the case of the US and the three...

The paper deals with estimation of both general GARCH as well as asymmetric EGARCH and TGARCH models, used to model the leverage effect of good news and bad news on market volatility. We estimate the models using daily returns of S&P 500 stock index and describe the news impact curves (NICs) for...

Hawkes Processes have been finding more applications in diverse areas of science, engineering and quantitative finance. In multi-frequency finance, various phenomena have been observed, such as shocks, crashes, volatility clustering, turbulent flows and contagion. Hawkes processes have been...