Time-Varying Risk Premium in Large Cross-Sectional Equity Datasets

70 Pages Posted: 18 Mar 2011 Last revised: 17 Apr 2018

See all articles by Patrick Gagliardini

Patrick Gagliardini

University of Lugano; Swiss Finance Institute

Elisa Ossola

University of Lugano

O. Scaillet

Swiss Finance Institute - University of Geneva

Date Written: October 2015

Abstract

We develop an econometric methodology to infer the path of risk premia from a 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 both instruments common to all assets and asset specific instruments. The estimator uses simple weighted two-pass cross-sectional regressions, and we show its consistency and asymptotic normality under increasing cross-sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no-arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi-period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousands US stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time-invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four-factor model capturing market, size, value and momentum effects.

Keywords: large panel, factor model, risk premium, asset pricing, sparsity, thresholding.

JEL Classification: C12, C13, C23, C51, C52 , G12

Suggested Citation

Gagliardini, Patrick and Ossola, Elisa and Scaillet, Olivier, Time-Varying Risk Premium in Large Cross-Sectional Equity Datasets (October 2015). Swiss Finance Institute Research Paper No. 11-40, Available at SSRN: https://ssrn.com/abstract=1786472 or http://dx.doi.org/10.2139/ssrn.1786472

Patrick Gagliardini

University of Lugano ( email )

Via Buffi 13
Lugano, TN 6900
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Elisa Ossola

University of Lugano ( email )

Via Giuseppe Buffi 13
Lugano, TN Ticino 6900
Switzerland

Olivier Scaillet (Contact Author)

Swiss Finance Institute - University of Geneva ( email )

Geneva
Switzerland

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