The Adaptive Dynamics of the Halloween Effect: Evidence from a 120-Year Sample from a Small European Market - Lobao, J (2023)
The Halloween effect predicts that stock markets in the winter months (November through April) generate significantly higher returns than in the summer months (May through October). This paper examines the time-varying behavior of the Halloween effect within a new historical dataset that covers about 120 years of Portuguese stock market history. We combine subsample analysis with rolling window analysis to show that the performance of the anomaly has varied in an adaptive fashion over time. The anomaly existed during the first four decades of the 20th century. Afterward, it vanished for 60 years, reappearing only at the beginning of the 21st century. However, in the first two decades of the new century, the effect seems to be a mere reflection of the excess return generated in January. Overall, the time-varying performance of the Halloween effect supports the adaptive market hypothesis for the Portuguese stock market.