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Real-Time Detection of Local No-Arbitrage Violations

Author

Listed:
  • Torben G. Andersen
  • Viktor Todorov
  • Bo Zhou

Abstract

This paper focuses on the task of detecting local episodes involving violation of the standard It\^o semimartingale assumption for financial asset prices in real time that might induce arbitrage opportunities. Our proposed detectors, defined as stopping rules, are applied sequentially to continually incoming high-frequency data. We show that they are asymptotically exponentially distributed in the absence of Ito semimartingale violations. On the other hand, when a violation occurs, we can achieve immediate detection under infill asymptotics. A Monte Carlo study demonstrates that the asymptotic results provide a good approximation to the finite-sample behavior of the sequential detectors. An empirical application to S&P 500 index futures data corroborates the effectiveness of our detectors in swiftly identifying the emergence of an extreme return persistence episode in real time.

Suggested Citation

  • Torben G. Andersen & Viktor Todorov & Bo Zhou, 2023. "Real-Time Detection of Local No-Arbitrage Violations," Papers 2307.10872, arXiv.org.
  • Handle: RePEc:arx:papers:2307.10872
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    References listed on IDEAS

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