A Dynamic Network of Arbitrage Characteristics
Shuyi Ge,
Shaoran Li and
Oliver Linton
Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
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 (search for similar items in EconPapers)
JEL-codes: C14 G11 G12 (search for similar items in EconPapers)
Date: 2020-06-29
New Economics Papers: this item is included in nep-net and nep-ore
Note: obl20, sl736, sg751
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2060
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