Nonlinear limits to arbitrage

Jingzhi Chen, Charlie Cai, robert faff, Yongcheol Shin

Research output: Contribution to journalArticlepeer-review


We study the nonlinear limits to arbitrage in a model. When mispricing is small,
arbitrage activity increases with mispricing because of the higher cost‐adjusted
return. However, at high levels of mispricing, arbitrageurs are deterred by larger
mispricing as funding constraints become more binding. Testing the model predictions on the index spot‐futures arbitrage with a Markov‐switching model, we
document an inverse U‐shaped relationship between mispricing and arbitrage
activity. The extreme regime is with the largest mispricing but least arbitrage
activity, and coincides with the market turmoil, suggesting that funding constraints
become the main driver behind the limit to arbitrage.
Original languageEnglish
Pages (from-to)1084-1113
JournalThe Journal of Futures Markets
Issue number6
Early online date28 Feb 2022
Publication statusPublished - Jun 2022

Bibliographical note

© 2022 The Authors


  • index arbitrage, limits to arbitrage, Markov‐switching GECM, mispricing correction, noise momentum

Cite this