Modeling local trends with regime shifting models with time-varying probabilities

被引：3
|
作者：
Focardi, Sergio M. [1 ]
Fabozzi, Frank J. [2 ]
Mazza, Davide [1 ]
机构：
[1] Pole Univ De Vinci, Res Ctr, Courbevoie, France
[2] EDHEC Business Sch, 57 S Main St, Doylestown, PA 18901 USA
来源：
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS | 2019年 / 66卷
关键词：
Regime shifting; Hidden Markov models; Duration-dependent Markov switching models; Return models; Momentum; Reversals; STYLIZED FACTS; SERIES; RETURNS; PRICES; BULL;
D O I：
10.1016/j.irfa.2019.06.007
中图分类号：
F8 [财政、金融];
学科分类号：
0202 ;
摘要：
In this paper we show that persistence and switching of trends are phenomena that appear in most long-lived stock return series. We model stock returns using a family of models based on hidden Markov models with duration-dependent transition probabilities. Trends are correlated so that aggregates such as indexes exhibit the same persistence and switching behavior as single stocks themselves. Hidden Markov models can thus explain medium-term momentum.
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页数：11
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