Detailed study of a moving average trading rule

We present a detailed study of the performance of a trading rule that uses moving average of past returns to predict future returns on stock indexes. Our main goal is to link performance and the stochastic process of the traded asset. Our study reports short, medium and long term effects by looking...

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Bibliographic Details
Published in:arXiv.org 2019-06
Main Authors: Ferreira, Fernando F, Silva, A Christian, Ju-Yi, Yen
Format: Article
Language:English
Subjects:
Autocorrelation
Distribution functions
Drift
Economic models
Long term effects
Performance indices
Probability distribution functions
Stochastic processes
Online Access:Get full text
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Summary:We present a detailed study of the performance of a trading rule that uses moving average of past returns to predict future returns on stock indexes. Our main goal is to link performance and the stochastic process of the traded asset. Our study reports short, medium and long term effects by looking at the Sharpe ratio (SR). We calculate the Sharpe ratio of our trading rule as a function of the probability distribution function of the underlying traded asset and compare it with data. We show that if the performance is mainly due to presence of autocorrelation in the returns of the traded assets, the SR as a function of the portfolio formation period (look-back) is very different from performance due to the drift (average return). The SR shows that for look-back periods of a few months the investor is more likely to tap into autocorrelation. However, for look-back larger than few months, the drift of the asset becomes progressively more important. Finally, our empirical work reports a new long-term effect, namely oscillation of the SR and propose a non-stationary model to account for such oscillations.
ISSN:2331-8422
DOI:10.48550/arxiv.1907.00212