In empirical finance and in time series applied economics in general, the least squares model is the workhorse. In class there is much discussion of the assumptions of exogeneity, homoskedasticity and serial correlation. However in practice it may be unstable regression coefficients that are...

Building models for high dimensional portfolios is important in risk management and asset allocation. Here we propose a novel and fast way of estimating models of time-varying covariances that overcome an undiagnosed incidental parameter problem which has troubled existing methods when applied...

The volatility term structure (VTS) reflects market expectations of average asset volatility over different time horizons. Various stochastic volatility models provide forecasts of the VTS and how it shifts in response to changes in market conditions. This paper develops a methodology for...

The Multiplicative Error Model introduced by Engle (2002) for positive valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multivariate extension of such a model, by taking into...

We introduce a new model to measure unconditional volatility, the Spline-GARCH. The model is applied to equity markets for 50 countries for up to 50 years of daily data. Macroeconomic determinants of unconditional volatility are investigated. It is found that volatility in macroeconomic factors...

The volatility term structure (VTS) reflects market expectations of asset volatility over different horizons. These expectations change over time, giving dynamic structure to the VTS. This paper evaluates volatilitymodels on the basis of their performance in hedging option price changes due to...

This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a time-varying pricing kernel, which is referred to as the empirical pricing kernel (EPK). The empirical pricing kernel is the preference function that rationalizes a...

This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a daily semi-parametric pricing kernel. The two key features of this estimator are: (1) the functional form of the pricing kernel is estimated semi-parametrically, instead of...

In this paper, we develop the theoretical and empirical properties of a new class of multivariate GARCH models capable of estimating large time-varying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance...

Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models...