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Faculty of Economics

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Ge, S., Li, S. and Linton, O.

A Dynamic Network of Arbitrage Characteristics


Abstract: We propose an asset pricing factor model constructed with semi-parametric characteristics-based mispricing and factor loading functions. This model captures common movements of stock excess returns and includes a two-layer network of arbitrage returns interconnected by security-specific characteristics. We approximate the unknown functions by B-splines where the number of B-splines coefficients is diverging. We estimate this model and test the existence of the mispricing function by a power enhanced hypothesis test. The enhanced test solves the low power problem caused by diverging B-spline coefficients. Meanwhile, the strengthened power approaches to one asymptotically. And the dynamic networks are explored through Hierarchical K-Means Clusterings from detected mispricing functions. We apply our methodology to CRSP monthly data for the US stock market with one-year rolling windows during 1967-2017. This empirical study shows the presence of mispricing functions in certain time blocks and a dynamic network structure of arbitrage returns through groups of some characteristics.

Keywords: Semiparametric, Characteristics-based, Network, Power-enhanced test

JEL Codes: C14 G11 G12

Author links: Oliver Linton  Shuyi Ge