 The Predictability of cay and cayMS for Stock and Housing Returns: A Nonparametric Causality in Quantile TestMehmet 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) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201577 Access Statistics for this paper More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC. |
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