Spatial Dependence in Asset Pricing Models

37 Pages Posted: 30 Sep 2016

See all articles by Bing Zhu

Bing Zhu

University of Reading - Henley Business School

Stanimira Milcheva

University College London

Date Written: September 27, 2016

Abstract

When analyzing asset prices in isolation, the classical asset pricing models only account for the time-series variation of the asset with the factors. However, valuable information would be lost if some cross-sectional dependence exists across the assets. We extend the factor model in Fama and French (2012) to account for spatial dependence across returns and estimate a spatial factor model. We model the spatial linkages using a measure of physical distance between the properties of listed real estate companies. We find that the spatial factor model is not rejected and the spatial parameter is significant. The spatial factor model performs better than the factor model, substantially improving the model fit. Proximity across the property holdings of real estate companies can predict higher return correlation across the firms, controlling for size, book-to-market, and momentum characteristics.

Keywords: Spatial factor model, asset pricing, listed real estate companies, weight matrix.

JEL Classification: G12, C30

Suggested Citation

Zhu, Bing and Milcheva, Stanimira, Spatial Dependence in Asset Pricing Models (September 27, 2016). Available at SSRN: https://ssrn.com/abstract=2844246 or http://dx.doi.org/10.2139/ssrn.2844246

Bing Zhu

University of Reading - Henley Business School ( email )

Greenlands
Henley, RG9 3AU
United Kingdom

Stanimira Milcheva (Contact Author)

University College London ( email )

1-19 Torrington Place
Department of Construction and Project Management
London, London WC1E 7HB
United Kingdom

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