Estimation of Large Dimensional Conditional Factor Models in Finance

76 Pages Posted: 28 Aug 2019 Last revised: 14 Sep 2019

See all articles by Patrick Gagliardini

Patrick Gagliardini

USI Università della Svizzera italiana; Swiss Finance Institute

Elisa Ossola

European Commission, Joint Research Centre

O. Scaillet

University of Geneva GSEM and GFRI; Swiss Finance Institute; University of Geneva - Research Center for Statistics

Date Written: August 27, 2019

Abstract

This chapter provides an econometric methodology for inference in large-dimensional conditional factor models in finance. Changes in the business cycle and asset characteristics induce time variation in factor loadings and risk premia to be accounted for. The growing trend in the use of disaggregated data for individual securities motivates our focus on methodologies for a large number of assets. The beginning of the chapter outlines the concept of approximate factor structure in the presence of conditional information, and develops an arbitrage pricing theory for large-dimensional factor models in this framework. Then we distinguish between two different cases for inference depending on whether factors are observable or not. We focus on diagnosing model specification, estimating conditional risk premia, and testing asset pricing restrictions under increasing cross-sectional and time series dimensions. At the end of the chapter, we review some of the empirical findings and contrast analysis based on individual stocks and standard sets of portfolios. We also discuss the impact on computing time-varying cost of equity for a firm, and summarize differences between results for developed and emerging markets in an international setting.

Keywords: large panel, factor model, conditional information, risk premium, asset pricing, emerging markets

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

Suggested Citation

Gagliardini, Patrick and Ossola, Elisa and Scaillet, Olivier, Estimation of Large Dimensional Conditional Factor Models in Finance (August 27, 2019). Swiss Finance Institute Research Paper No. 19-46. Available at SSRN: https://ssrn.com/abstract=3443426 or http://dx.doi.org/10.2139/ssrn.3443426

Patrick Gagliardini

USI Università della Svizzera italiana ( 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

European Commission, Joint Research Centre ( email )

Belgium

Olivier Scaillet (Contact Author)

University of Geneva GSEM and GFRI ( email )

40 Boulevard du Pont d'Arve
Geneva 4, 1211
Switzerland
+ 41 22 379 88 16 (Phone)
+41 22 389 81 04 (Fax)

HOME PAGE: http://www.scaillet.ch

Swiss Finance Institute

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

University of Geneva - Research Center for Statistics

Geneva
Switzerland

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