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

A Dynamic Network of Arbitrage Characteristics

WP Number: 2058

Abstract: We propose an asset pricing factor model constructed with semi-parametric characteristics-based mispricing and factor loading functions. We approximate the unknown functions by B-splines sieve 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, with the strengthened power approaches to one asymptotically. We also investigate the structure of mispricing components through Hierarchical K-means Clusterings. We apply our methodology to CRSP (Center for Research in Security Prices) and FRED (Federal Reserve Economic Data) 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. We also find that distinct clusters of the same characteristics lead to similar arbitrage returns, forming a "peer group" of arbitrage characteristics.

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

JEL Codes: C14 G11 G12

Author links: Oliver Linton  

PDF: wp2058.pdf

Open Access Link: 10.17863/CAM.61819

Theme: empirical