Do cay and cay^MS predict stock and housing returns? Evidence from a nonparametric causality test

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• 作者：Mehmet Balcilar^a ; ^b ; ^{mehmet@mbalcilar.net} ; Rangan Gupta^b ; ^{Rangan.Gupta@up.ac.za} ; Ricardo M. Sousa^c ; ^d ; ^{rjsousa@eeg.uminho.pt} ; Mark E. Wohar^e ; ^f ; ^{mwohar@mail.unomaha.edu}
• 关键词：C22 ; C32 ; C53 ; Q41
• 刊名：International Review of Economics & Finance
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：48
• 期：Complete
• 页码：269-279
• 全文大小：931 K
• 卷排序：48

文摘

We use a nonparametric causality-in-quantiles test to compare the predictive ability of the consumption-wealth ratio (cay) and the Markov Switching version (cayMS) for excess and real stock and housing returns and their volatility. Our results reveal strong evidence of nonlinearity and regime changes in the relationship between asset returns and cay or cayMS, which corroborates the relevance of this econometric framework. Moreover, both cay or cayMS are found to predict only excess stock returns over its entire conditional distribution, with the latter being a strong predictor only at certain quantiles. As for the housing market, these two consumption-wealth ratios only predict the volatility of real housing returns, with cayMS outperforming cay over the majority of the conditional distribution.