Dynamic Peer Groups of Arbitrage Characteristics

50 Pages Posted: 21 Jul 2020 Last revised: 7 Jun 2021

See all articles by Shaoran Li

Shaoran Li

Peking University

Oliver B. Linton

University of Cambridge

Shuyi Ge

Nankai University - Department of Finance

Date Written: June 29, 2020

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; Peer Groups; Power-enhanced Test

JEL Classification: C14, G11, G12

Suggested Citation

Li, Shaoran and Linton, Oliver B. and Ge, Shuyi, Dynamic Peer Groups of Arbitrage Characteristics (June 29, 2020). Available at SSRN: https://ssrn.com/abstract=3638105 or http://dx.doi.org/10.2139/ssrn.3638105

Shaoran Li (Contact Author)

Peking University ( email )

5 Yiheyuan Road
Beijing, 100871
China

Oliver B. Linton

University of Cambridge ( email )

Faculty of Economics
Cambridge, CB3 9DD
United Kingdom

Shuyi Ge

Nankai University - Department of Finance ( email )

94 Weijin Road
Tianjin, 300071
China

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