Combining low-volatility and mean-reversion anomalies: Better together?

IF 0.3 Q4 BUSINESS, FINANCE Algorithmic Finance Pub Date : 2023-11-27 DOI:10.3233/af-220441
Eero J. Pätäri, Sheraz Ahmed, Tuomas Lankinen, J. Yeomans
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Abstract

This paper contributes to the existing stock market anomaly literature by being the first to analyze the benefits of combining two distinct anomalies; specifically, the low-volatility and mean-reversion anomalies. Our results show that on a long-only basis, these two time-varying anomalies could be combined into a double-sort investment strategy that includes some desirable characteristics from each of them, thereby making the portfolio return accumulation more stable over time. As the added-value of low-volatility investing stems mostly from the risk-reduction side, while contrarian stocks are generally highly volatile with remarkable upside potential, the use of the double-sort portfolio-formation in which the contrarian stocks are picked from the sub-set of below-median volatility stocks can shorten the below-market performance periods that have occasionally materialized for plain low-volatility or plain contrarian investors.
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结合低波动性和均值回复异常:结合得更好?
本文首次分析了将两种不同的异常现象(即低波动性异常现象和均值回复异常现象)结合起来的益处,为现有的股市异常现象文献做出了贡献。我们的研究结果表明,在长期纯粹的基础上,这两种时变异常现象可以结合成一种双重排序投资策略,其中包含了这两种异常现象各自的一些理想特征,从而使投资组合的回报积累随着时间的推移更加稳定。由于低波动性投资的附加值主要来自于降低风险方面,而逆向投资股票一般波动性较高,具有显著的上涨潜力,因此使用双重排序投资组合构建,从低于中位波动性股票的子集中挑选逆向投资股票,可以缩短普通低波动性或普通逆向投资投资者偶尔出现的低于市场表现的时期。
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来源期刊
Algorithmic Finance
Algorithmic Finance BUSINESS, FINANCE-
CiteScore
0.40
自引率
0.00%
发文量
6
期刊介绍: Algorithmic Finance is both a nascent field of study and a new high-quality academic research journal that seeks to bridge computer science and finance. It covers such applications as: High frequency and algorithmic trading Statistical arbitrage strategies Momentum and other algorithmic portfolio management Machine learning and computational financial intelligence Agent-based finance Complexity and market efficiency Algorithmic analysis of derivatives valuation Behavioral finance and investor heuristics and algorithms Applications of quantum computation to finance News analytics and automated textual analysis.
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