Dissecting Anomalies: the Case of the Russian Stock Market

The aim of this thesis is to dissect anomalies on the Russian market of common stocks from 2007 to 2015. The data sample consists of 214 nonfinancial companies. The following variables are checked for the presence of anomaly nature: size, book to market ratio, price to earnings ratio, past returns. Two common ways for identifying anomalies are used: sorts of returns on anomaly variables with time-series testing of the CAPM model and cross-section regressions of Fama and MacBeth (1973) with anomaly variables used as explanatory ones. It is shown that big companies with low book to market ratio brings higher risk-adjusted returns. The portfolio with micro stocks which are past month losers generates negative abnormal returns. Indicators associated with the price to earnings ratio and past month returns help to explain the cross-section difference in returns of all companies. The size effect becomes significant when only micro companies are considered.