Does climatic seasonality produce seasonality in stock returns? Evidence from an emerging stock market

This paper investigates seasonality in the Kuwait stock market using monthly average data on the market index covering the period 1996-2005. While conventional regression analysis fails to detect seasonality, structural time series modelling reveals a significant June seasonal as well as the stochastic nature of seasonality. The main explanation put forward for this phenomenon is that harsh climatic conditions in the summer months of July and August forces a significant proportion of the Kuwaiti population (and hence stock traders) to leave the country for overseas holidays. Before leaving the country, traders accumulate stocks, putting upward pressure on prices and creating the June effect.