 Can (unusual) weather conditions in New York predict South African stock returns?Nicholas Apergis () and Rangan Gupta Research in International Business and Finance, 2017, vol. 41, issue C, 377-386 Abstract: This paper investigates the explanatory power of certain weather variables, measured as deviations from their monthly averages, in a leading international financial trading centre, i.e., New York, for South African stock returns, over the daily period January 2nd, 1973 to December, 31, 2015. The empirical results highlight that these unusual deviations of weather variables have a statistically significant negative effect on the stock returns in South Africa, indicating that unusual weather conditions in New York can be used to predict South African stock returns, which otherwise seems to be highly unpredictable. In fact, a forecasting exercise recommends that a trading rule that considers those weather variables through a GARCH modelling approach seems to outperform the random walk model and thus beat the market. Keywords: Unusual weather conditions; New York weather; South African stock market (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:41:y:2017:i:c:p:377-386 DOI: 10.1016/j.ribaf.2017.04.052 Access Statistics for this article Research in International Business and Finance is currently edited by T. Lagoarde Segot More articles in Research in International Business and Finance from Elsevier |
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