We employ a multivariate BEKK GARCH model which allows news to affect conditional volatility in an asymmetric manner. The asymmetric model outperforms the standard symmetric model, implying that efficient financial decision makers should not treat good and bad news as homogenous. We estimate the conditional variance and covariance of the Japanese yen, Swiss franc and British pound vis-à-vis the...

This note investigates long-run exclusion in a cointegrated vector autoregressive (VAR) model from the viewpoint of …nite-sample statistical inference. Monte Carlo experiments show that, in various circumstances, a mis-speci…ed partial VAR model, which is justi…ed by the existence of a long-run excluded variable, can lead to better …nite-sample inference for cointegrating rank than a fully-spec...

Gaussian vector autoregressive (VAR) processes have been extensively studied in the literature. However, Gaussian assumptions are stringent for heavy-tailed time series that frequently arises in finance and economics. In this paper, we develop a unified framework for modeling and estimating heavy-tailed VAR processes. In particular, we generalize the Gaussian VAR model by an elliptical VAR mode...

Ait-Sahalia and Lo (2000) and Panigirtzoglou and Skiadopoulos (2004) have argued that Economic VaR (E-VaR), calculated under the option market implied risk neutral density is a more relevant measure of risk than historically based VaR. As industry practice requires VaR at high confidence level of 99%, we propose Extreme Economic Value at Risk (EE-VaR) as a new risk measure, based on the General...

Value-at-risk (VaR) has become the standard criterion for assessing risk in the financial industry. Given the widespread usage of VaR, it becomes increasingly important to study the effects of VaR-based risk management on the prices of stocks and options. We solve a continuous-time asset pricing model, based on Lucas (1978) and Basak and Shapiro (2001), to investigate these effects. We find tha...

This paper applies the hybrid dynamic general-equilibrium, vector autoregressive (DGE-VAR) model developed by Ireland (1999) to Canadian time series. It presents the first Canadian evidence that a hybrid DGE-VAR model may have better out-of-sample forecasting accuracy than a simple, structure-free VAR model. The evidence suggests that estimated DGE models have the potential to add good forecast...

Vector Autoregression Models (VAR) are widely used by researchers to capture the linear interdependencies among multiple time series. We propose a novel method called Clustered VAR (CVAR) to identify components of the data generated by a mixture of K VAR processes. By applying a CVAR model to a consumer-level time series dataset on shopping behavior at a retailer, we segment consumers based on ...

JEL classification: E32 C32 How similar is the price behavior of oil, natural gas, and coal? Are there any interactions among these three fuel prices and their volatilities? Using the Yatchew and Dimitropoulos (2016) annual data for the United States, over the period from 1870 to 2014, and state-of-the-art econometric methodology, we explore for spillovers and interactions among the three energ...