We develop an econometric methodology to infer the path of risk premia from large unbalanced panel of individual stock returns. We estimate the time-varying risk premia implied by conditional linear asset pricing models where the conditioning includes instruments common to all assets and asset...

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

Testing procedures for predictive regressions with lagged autoregressive variables imply a suboptimal inference in presence of small violations of ideal assumptions. We propose a novel testing framework resistant to such violations, which is consistent with nearly integrated regressors and...

Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies in different asset classes. Despite the popularity of portfolio sorting, little attention has been paid to the statistical properties of the procedure or to the...

This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using...

We find that weak identification can lead to econometric problems with Fama-MacBeth regressions, including serious size distortions and biased point estimates. Two sources of weak identification are particularly important and have been little studied in the finance literature – small betas and...

In this paper we investigate asymmetries in time-varying means, volatilities, correlations, and betas of equity returns in a multivariate threshold framework. We consider alternative specifications in which the threshold variable is based on well-established equity pricing factors and...

Two of the most important stylized facts well-known in finance relate to the non-Gaussian distribution and to the volatility clustering of stock returns. In this paper, we show that a new class of stochastic processes – called Multifractional Processes with Random Exponent (MPRE) – can...

The scaling properties of two alternative fractal models recently proposed to characterize the dynamics of stock market prices are compared. The former is the Multifractal Model of Asset Return (MMAR) introduced in 1997 by Mandelbrot, Calvet and Fisher in three companion papers. The latter is...