Photo by the author Introduction In this article, we review the infamous January effect which proposes that stocks' prices increase from December to January is the highest. We illustrate the causes of the January effect, and present a simple trading strategy to profit from this calendar effect. The project is shared on my online repository … Continue reading Revisiting The January Effect
Photo by the author Introduction Principal component analysis (PCA) is a statistical technique which enjoys applications in image processing and quantitative finance. In this article, we focus on the later application in quantitative trading, in particular using PCA as a multi-factor model of portfolio returns. We use the multi-factor model to design a momentum trading … Continue reading Principal Component Analysis As A Factor Model
A time series is considered stationary if its probability distribution does not change over time. If the price series of a security is stationary, then it would be a suitable candidate for a mean-reversion trading strategy. However, most security price series are not stationary: they seem to follow a lognormal random walk; and drift farther and farther away from the initial value.