Linear Factor Models in Finance

Chapter 2: Estimating UK Factor Models Using the Multivariate Skew Normal Distribution

C. J. Adcock [*]

Abstract

This chapter describes a factor model, which is derived using the multivariate skew normal distribution. This is an attractive model for applications in finance because it is a tractable multivariate distribution which includes skewness. The model posits that asset returns and factors have a joint multivariate skew normal distribution. The factor model itself is derived formally from conditional distribution of asset returns given factors. This provides several new theoretical insights into the relationship between asset returns and factors. Most notable of these is that the sensitivity of asset returns to factors is not measured by the conventional regression coefficients. Another interesting feature is that the factor model contains a component that is a non-linear function of the factor values. According to results of this study of UKFTSE250 stocks, the multivariate skew normal distribution offers an improved fit when compared to the use of the multivariate normal distribution. The MSN factor model offers different measures of sensitivity to the linear effects of the chosen factors as well as a time-varying non-linear component.

[*] The University of Sheffield, UK.

2.1 Introduction

Linear factor models are used universally within the finance community. They have a long and distinguished pedigree which dates back to major theoretical papers, like those by Sharpe (1964) and Ross (1976). In the 1960s and 1970s, factor models were the subject of papers by many authors, including King (1966) and Rosenberg and his co-workers, see Rosenberg and Marathe (1975, 1976), to name but three...

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