Abstract

The effects of the weather in Sydney on the daily returns of two stock indices of the Australian stock exchange are investigated. Three factors capture the essence of daily variations in temperature, cloud cover and wind speed. Two steps are taken to increase the efficiency of the statistical tests. First, control variables are incorporated in the regression models to abstract systematic variance from the error terms. Second, a repeated measures design is used to estimate the standard errors of the slope coefficients. The returns of the stock indices are uninfluenced by wind speed and cloud cover. However, the returns of the two stock indices are negatively influenced by the temperature in Sydney. There is evidence that deseasonalized temperature has a stronger negative influence than the level of temperature.

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