The paper examines the presence of risk spillover to US travel & leisure industry from extreme changes in uncertainties. More specifically, using a time-varying copula based conditional Value-at-Risk (CoVaR) framework, we evaluate dynamic impact uncertainties on by taking into consideration uncertainty economic policy, equity market conditions, and crude oil prices. findings indicate signif...

This paper proposes a high dimensional factor multivariate stochastic volatility (SVOL) model in which factor covariance matrices are driven by Wishart random processes. The framework allows for unrestricted specification of intertemporal sensitivities, which can capture the persistence in volatilities, kurtosis in returns, as well as correlation breakdowns and contagion effects in volatilities...

Article history: Received 23 August 2011 Received in revised form 16 April 2012 Accepted 19 April 2012 Available online 5 May 2012 This paper proposes a two-state Markov-switching model for stock market returns in which the state-dependent expected returns, their variance and associated regime-switching dynamics are allowed to respond to market information. More specifically, we apply this mode...

The concept of causality is naturally defined in terms of conditional distribution, however almost all the empirical works focus on causality in mean. This paper aim to propose a nonparametric statistic to test the conditional independence and Granger non-causality between two variables conditionally on another one. The test statistic is based on the comparison of conditional distribution funct...

We use high-frequency data to study the dynamic relationship between volatility and equity returns. We provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage effect and the volatility feedback effect. The leverage hypothesis asserts that return shocks lead to changes in conditional volatility, while the volatility feedback effect theory assu...

We generalize an asset pricing model based on the Arbitrage Pricing Theory (APT) allowing beta to be time-varying. Making beta a random variable adds flexibility to the model because permits a non-linear relation between individual returns and the set of factors, and accounts for the effect of possible omitted variables. We integrate the conditional APT with a general linear stochastic process ...

Second moments of asset returns are important for risk management and portfolio selection. The problem of estimating second moments can be approached from two angles: time series and the cross-section. In time series, the key is to account for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH/GARCH family started by Engle (1982). In ...

Volatility of a stock may incur a risk premium, leading to a positive correlation between volatility and returns. On the other hand the leverage effect, whereby negative returns increase volatility, acts in the opposite direction. We propose a reformulation and extension of the ARCH in Mean model, in which the logarithm of scale is driven by the score of the conditional distribution. This EGARC...

Modelling Realized Variance when Returns are Serially Correlated by Roel C. A. Oomen* This article examines the impact of serial correlation in high frequency returns on the realized variance measure. In particular, it is shown that the realized variance measure yields a biased estimate of the conditional return variance when returns are serially correlated. Using 10 years of FTSE-100 minute by...

We focus on the pairwise correlations of Japanese stock returns to study their correlation dynamics empirically. Two types of reduced size sample portfolios are created to observe the changes in conditional correlation: a set of individual stock portfolios created by using a network-based clustering algorithm and a single portfolio created from the mean return indexes of the individual sample p...