We develop a new stochastic volatility model that captures the three most important features of stock index returns: negative correlation between returns and future volatility, excess kurtosis and negative skewness. We estimate the model parameters by maximum likelihood using a numerical...

We evaluate the performance of several specification tests for Markov regime-switching time series models. We consider the Lagrange Multiplier and dynamic specification tests of Hamilton (1994) and Ljung-Box tests based on both the generalized residual and a standard-normal residual constructed...

We develop a model of stock return volatility that includes a positive risk-return relation, a significant volatility feedback effect and explains a rich set of empirical phenomena. It explains the negative correlation between returns and volatility we observe in stock data. We find that...

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier and we...

We study the ability of traditional diagnostic tests and LM and CUSUM structural break tests to detect a range of different types of breaks in GARCH models. We find that Wooldridge's (1990) robust LM tests for autocorrelation and ARCH have no power to detect structural breaks in GARCH models....

This study finds that market's underreaction to good news is a driver of Gutierrez and Kelly's (2008) weekly momentum returns. By employing a dataset of 10.1 million news items in four regions (the U.S., Europe, Japan, and Asia Pacific), we find that stocks having important and positive news...

We explore the impact of delisting on the performance of the momentum trading strategy in Australia. We employ a new dataset of hand-collected delisting returns for all Australian stocks and provide the first study outside the U.S. to jointly examine the effects of delisting and missing returns...

We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying...

A pervasive and puzzling feature of banks' Value at Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among...

In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR disclosure index that captures many different facets of market...