英文标题：
《Detailed study of a moving average trading rule》
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作者：
Fernando F. Ferreira, A. Christian Silva, Ju-Yi Yen
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最新提交年份：
2019
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英文摘要：
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.
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中文摘要：
我们对交易规则的表现进行了详细研究，该规则使用过去收益的移动平均值来预测股票指数的未来收益。我们的主要目标是将绩效与交易资产的随机过程联系起来。我们的研究通过观察夏普比率（SR）报告了短期、中期和长期影响。我们将交易规则的夏普比率计算为基础交易资产概率分布函数的函数，并将其与数据进行比较。我们表明，如果绩效主要是由于交易资产的收益存在自相关，则SR作为投资组合形成期（回顾）的函数与漂移（平均收益）导致的绩效非常不同。SR表明，在几个月的回顾期内，投资者更有可能利用自相关。然而，对于几个月以上的回顾，资产的漂移变得越来越重要。最后，我们的经验工作报告了一个新的长期效应，即SR的振荡，并提出了一个非平稳模型来解释这种振荡。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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