Statistical arbitrage: factor investing approach

Date
2023-09-16
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OR Spectrum
Print ISSN
0171-6468
Electronic ISSN
1436-6304
Publisher
Springer Science and Business Media Deutschland GmbH
Volume
45
Issue
4
Pages
1295 - 1331
Language
en_US
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Abstract

We introduce a continuous time model for stock prices in a general factor representation with the noise driven by a geometric Brownian motion process. We derive the theoretical hitting probability distribution for the long-until-barrier strategies and the conditions for statistical arbitrage. We optimize our statistical arbitrage strategies with respect to the expected discounted returns and the Sharpe ratio. Bootstrapping results show that the theoretical hitting probability distribution is a realistic representation of the empirical hitting probabilities. We test the empirical performance of the long-until-barrier strategies using US equities and demonstrate that our trading rules can generate statistical arbitrage profits. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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