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Dynamic Peer Groups of Arbitrage Characteristics

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  • Shuyi Ge
  • Shaoran Li
  • Oliver Linton

Abstract

We propose an asset pricing factor model constructed with semiparametric 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-splines coefficients, with the strengthened power approaching 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 Compustat data for the U.S. 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.

Suggested Citation

  • Shuyi Ge & Shaoran Li & Oliver Linton, 2024. "Dynamic Peer Groups of Arbitrage Characteristics," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 367-390, April.
    • Handle: RePEc:taf:jnlbes:v:42:y:2024:i:2:p:367-390
    DOI: 10.1080/07350015.2021.2011736
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