We develop a new multivariate generalized ARCH (GARCH) parameterization suitable for testing the hypothesis that the optimal futures hedge ratio is constant over time, given that the joint distribution of cash and futures prices is characterized by autoregressive conditional heteroskedasticity (ARCH). The advantage of the new parameterization is that it allows for a flexible form of time-varyin...

This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy and encompassing applied to predictions from nested long-horizon regression models. We first derive the asymptotic distributions of a set of tests of equal forecast accuracy and encompassing, showing that the tests have non-standard distributions that depend on the parameters of the data-generati...

This paper develops a new methodology for estimating and testing conditional factor models in finance. We propose a two-stage procedure that naturally unifies the two existing approaches in the finance literature–the parametric approach and the nonparametric approach. Our combined approach possesses important advantages over both methods. Using our two-stage combined estimator, we derive new te...

A strong private equity market is a cornerstone for commercialization and innovation in modern economies. However, substantial differences exist in the relative amounts raised and invested in private equity across European countries. We investigate the macro-determinants of private equity investment in Europe, focusing on the comparison between CEE and Western European countries. Our estimation...

We propose a nonparametric likelihood ratio testing procedure for choosing between a parametric (likelihood) model and a moment condition model when both models could be misspecified. Our procedure is based on comparing the Kullback–Leibler Information Criterion (KLIC) between the parametric model and moment condition model. We construct the KLIC for the parametric model using the difference be...

In this paper, we examine the structural stability of predictive regression models of quarterly real stock returns over the postwar era. We consider predictive regressions models of S&P 500 and CRSP equal-weighted real stock returns based on eight financial variables that display predictive ability in the extant literature. We test for structural stability using the popular Andrews (1993) SupF ...

This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio management. Evaluation of volatility models is then considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for individual as well as ‘average’ mod...

In the presence of selection bias the traditional estimators for pseudo panel data models are inconsistent. This paper discusses a method to achieve consistency in static linear pseudo panels in the presence of selection bias and a testing procedure for sample selection bias. The authors’ approach uses a bias correction term proportional to the inverse Mills ratio with argument equal to the “no...

In this paper, I show that the variance of Fama-French factors, the variance of the momentum factor, as well as the correlation between these factors, predict an important fraction of the timeseries variation in post-1990 aggregate stock market returns. This predictability is particularly strong from one month to one year, and it dominates that afforded by the variance risk premium and other po...