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文件名:  On_the_Profitability_of_Optimal_Mean_Reversion_Trading_Strategies.pdf
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英文标题:
《On the Profitability of Optimal Mean Reversion Trading Strategies》
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作者:
Peng Huang, Tianxiang Wang
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最新提交年份:
2016
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英文摘要:
We study the profitability of optimal mean reversion trading strategies in the US equity market. Different from regular pair trading practice, we apply maximum likelihood method to construct the optimal static pairs trading portfolio that best fits the Ornstein-Uhlenbeck process, and rigorously estimate the parameters. Therefore, we ensure that our portfolios match the mean-reverting process before trading. We then generate contrarian trading signals using the model parameters. We also optimize the thresholds and the length of in-sample period by multiple tests. In nine good pair examples, we can see that our pairs exhibit high Sharpe ratio (above 1.9) over the in-sample period and out-of-sample period. In particular, Crown Castle International Corp. (CCI) and HCP, Inc. (HCP) achieve a Sharpe ratio of 2.326 during in-sample period and a Sharpe ratio of 2.425 in out-of-sample test. Crown Castle International Corp. (CCI) and Realty Income Corporation (O) achieve a Sharpe ratio of 2.405 and 2.903 respectively during in-sample period and out-of-sample period.
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中文摘要:
我们研究了美国股市中最优均值回归交易策略的盈利能力。与常规配对交易不同,我们采用最大似然法构造了最符合Ornstein-Uhlenbeck过程的最优静态配对交易组合,并严格估计了参数。因此,我们确保我们的投资组合在交易前符合均值回复过程。然后,我们使用模型参数生成反向交易信号。我们还通过多次测试优化了阈值和采样周期长度。在九个好的配对示例中,我们可以看到我们的配对在样本内和样本外期间表现出较高的夏普比(高于1.9)。特别是,Crown Castle International Corp.(CCI)和HCP,Inc.(HCP)在样本期内达到2.326的夏普比,在样本外测试中达到2.425的夏普比。Crown Castle International Corp.(CCI)和Realty Income Corporation(O)在样本期内和样本期外的夏普比率分别为2.405和2.903。
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分类信息:

一级分类:Quantitative Finance 数量金融学
二级分类:Portfolio Management 项目组合管理
分类描述:Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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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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