Economics at your fingertips  

The Predictability of cay and cayMS for Stock and Housing Returns: A Nonparametric Causality in Quantile Test

Mehmet Balcilar, Rangan Gupta, Ricardo Sousa and Mark Wohar ()

No 201577, Working Papers from University of Pretoria, Department of Economics

Abstract: We use a nonparametric causality-in-quantiles test to compare the predictive ability of cay and cayMS for excess and real stock and housing returns and their volatility using quarterly data for the US over the periods of 1952:Q1-2014:Q3 and 1953:Q2-2014:Q3 respectively. 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, we confirm the outperformance of cayMS vis-à-vis cay and their relevance for excess stock returns. Furthermore, we show that cayMS is particularly useful at forecasting certain quantiles of the conditional distribution. As for housing returns, the empirical evidence suggests that the predictive ability of cay and cayMS is relatively low. Yet, cay outperforms cayMS over the majority of the quantiles of the conditional distribution of the variance of real housing returns.

Keywords: stock returns; housing returns; quantile; nonparametric; causality (search for similar items in EconPapers)
JEL-codes: C32 C53 Q41 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2015-10
New Economics Papers: this item is included in nep-for and nep-ure
References: Add references at CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rangan Gupta ().

Page updated 2023-09-17
Handle: RePEc:pre:wpaper:201577