This paper considers correlation, models, and risk management in light of recent financial market events. It begins with a review of key contributing factors, then considers the role of liquidity in measuring default risk, and highlights some lessons learned from the experience as events...

Due to the current credit crisis, critical questions are being asked concerning some of the quantitative methods used in risk management under the Basel II proposals. In this paper I have given a critical look at Extreme Value Theory and Copulas. Both their potential applications and the...

This paper proposes new test statistics for the dependence and cross and auto covariance estimators of bivariate noise processes. It derives their asymptotic distributions and provides additional tests for the statistical significance of covariance estimators. Monte Carlo simulation shows that...

The paper proposes an additive cascade model of volatility components defined over different time periods. This volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering different volatility components realized over different time horizons and...

In this paper, we extend the concept of the news impact curve of volatility developed by Engle and Ng (1993) to the higher moments and co-moments of the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model with non-normal innovations. For this purpose, we present...

We study the sample estimation risk of the traditional Sharpe ratio without the restrictive assumption of normality for return series. We derive analytical results for the approximate bias and variance of the sample Sharpe ratio in terms of the underlying distribution parameters. The results...

We propose a completely kernel based method of estimating the call price function or the state price density of options. The new estimator of the call price function fulfills the constraints like monotonicity and convexity given in Breeden and Litzenberger (1978) without necessarily estimating...

This paper shows how independent component analysis can be used to estimate the generalized orthogonal GARCH model in a fraction of the time otherwise required. The proposed method is a two-step procedure, separating the estimation of the correlation structure from that of the univariate...

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005)...