英文标题：
《A Multi-factor Adaptive Statistical Arbitrage Model》
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作者：
Wenbin Zhang, Zhen Dai, Bindu Pan, Milan Djabirov
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最新提交年份：
2014
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英文摘要：
  This paper examines the implementation of a statistical arbitrage trading strategy based on co-integration relationships where we discover candidate portfolios using multiple factors rather than just price data. The portfolio selection methodologies include K-means clustering, graphical lasso and a combination of the two. Our results show that clustering appears to yield better candidate portfolios on average than naively using graphical lasso over the entire equity pool. A hybrid approach of using the combination of graphical lasso and clustering yields better results still. We also examine the effects of an adaptive approach during the trading period, by re-computing potential portfolios once to account for change in relationships with passage of time. However, the adaptive approach does not produce better results than the one without re-learning. Our results managed to pass the test for the presence of statistical arbitrage test at a statistically significant level. Additionally we were able to validate our findings over a separate dataset for formation and trading periods.
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中文摘要：
本文研究了基于协整关系的统计套利交易策略的实现，其中我们使用多个因素而不仅仅是价格数据来发现候选投资组合。投资组合选择方法包括K均值聚类、图形套索以及两者的组合。我们的结果表明，在整个股票池中，聚类似乎平均比单纯使用图形套索产生更好的候选投资组合。将图形套索和聚类结合使用的混合方法仍能产生更好的结果。我们还通过重新计算潜在投资组合一次，以考虑随着时间推移关系的变化，来检验交易期间适应性方法的效果。然而，自适应方法并不比不进行再学习的方法产生更好的结果。我们的结果在统计显著水平上通过了统计套利测试。此外，我们能够通过一个单独的数据集验证我们的发现，包括形成期和交易期。
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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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