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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)
JEL-codes: C22 G10 G15 (search for similar items in EconPapers)
Date: 2017
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