Structural instability and predictability

被引：9

作者：

Devpura, Neluka ^{[1
]}

Narayan, Paresh Kumar ^{[2
]}

Sharma, Susan Sunila ^{[2
,3
]}

机构：

[1] Univ Sri Jayewardenepura, Dept Stat, Nugegoda, Sri Lanka

[2] Deakin Business Sch, Ctr Financial Econometr, Melbourne, Vic, Australia

[3] Deakin Business Sch, Dept Finance, Melbourne, Vic, Australia

来源：

JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY | 2019年 / 63卷

关键词：

Structural break; Predictability; Monte Carlo simulation; STOCK RETURN PREDICTABILITY; EQUITY PREMIUM; DIVIDEND YIELDS; UNIT-ROOT; LONG;

D O I：

10.1016/j.intfin.2019.101145

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

We propose a structural break predictive regression model that accounts for predictor persistency, endogeneity, heteroscedasticity, and a structural break. Monte Carlo (MC) simulations indicate that this test performs satisfactorily compared to competitor estimators. We employ a popular U.S. data set (the period January 1927 to December 2016) that includes stock market returns and multiple predictors. We show, consistent with the MC results, evidence of a structural break. Our analysis reveals that a structural break-based predictive regression model fits the data reasonably well in predicting stock price returns. (C) 2019 Elsevier B.V. All rights reserved.

引用

页数：13

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