在意大利、英国、美国和墨西哥的股票投资组合中使用马尔可夫转换模型:一个性能测试

IF 0.6 Q4 STATISTICS & PROBABILITY
O. D. L. Torre, Evaristo Galeana-Figueroa, J. Álvarez‐García
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引用次数: 8

摘要

在本文中,我们测试了Markov切换模型在股票交易策略中的使用,继Brooks和Persand(2001)、Kritzman等人(2012)和Hauptmann等人(2014)之后,他们建议将其用作表现不佳时期的预警系统。我们通过在美国和英国市场再次测试(受交易费影响),并将我们的测试扩展到意大利和墨西哥的案例,来扩展他们的审查。我们的马尔可夫切换策略背后的基本原理是投资于低波动性或“表现良好”时期的股票指数跟踪ETF,以及投资于高波动率或“表现不佳”时期的本地无风险资产。我们的结果表明,在2001年1月4日至2017年7月30日的每周模拟中,我们的系统有助于在所有模拟市场中创建阿尔法,即使意大利的案例因金融或政治危机而出现了几个严重的困境时刻。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Markov-Switching models in Italian, British, U.S. and Mexican equity portfolios: a performance test
In this paper we test the use of Markov Switching models in equity trading strategies, following Brooks and Persand (2001), Kritzman et al. (2012) and Hauptmann et al. (2014), who suggest their use as warning systems of bad performing periods. We extend their reviews by testing again (with the impact of trading fees) the U.S. and U.K. markets and by extending our tests to the Italian and Mexican case. The rationale behind our Markov-Switching strategy is to invest in equity index tracking ETFs in low volatility or ”good performing” periods and in the local risk-free asset in high-volatility or ”bad performing” ones. Our results show that in a weekly simulation from January 4, 2001 to July 30, 2017 with a 0.35% trading fee plus taxes, our system is useful to create alpha in all the simulated markets even if the Italian case showed several deep distress moments due to a financial or political crisis.
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来源期刊
CiteScore
1.40
自引率
14.30%
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