Publication Type

Journal Article

Version

submittedVersion

Publication Date

7-2023

Abstract

Developing an excellent quantitative trading strategy to obtain a high Sharpe ratio requires optimizing several parameters at the same time. Example parameters include the window length of a moving average sequence, the choice of trading instruments, and the thresholds used to generate trading signals. Simultaneously optimizing all these parameters to seek a high Sharpe ratio is a daunting and time-consuming task, partly because of the unknown mechanism determining the Sharpe ratio. This article proposes using Bayesian optimization to systematically search for the optimal parameter configuration that leads to a high Sharpe ratio. The author shows that the proposed intelligent search strategy performs better than manual search, a common practice that proves to be inefficient. The author’s framework also can easily be extended to other parameter selection tasks in portfolio optimization and risk management.

Discipline

Finance | Finance and Financial Management

Research Areas

Quantitative Finance

Publication

Journal of Portfolio Management

Volume

49

Issue

7

First Page

1

Last Page

9

ISSN

0095-4918

Identifier

10.3905/jpm.2023.1.497

Publisher

Institutional Investor Inc

Additional URL

https://doi.org/10.3905/jpm.2023.1.497

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