A Note on the Predictability of the Russian Stock Market

Over the past 20 years, the problem of low investment activity of private investors has been . featuring the Russian stock market. There are various reasons . for that, among them the. financial crises, limited access to information, a high subjectivity and lack of developed and simple methods. for making investment decisions. Therefore, this research aims to study the predictability of the Russian stock market in the conditions of instability due to crises, as well as the limited access of private investors to information and the low investment literacy in general. This research addresses the predictability of the equity premium on the Russian stock market. from 31 January 2008 to 31 January 2017. This is the period of two economic crises. for the Russian economy: . from 2008 to 2013 and. from 2014 to 2017. The authors investigate whether the returns of industry portfolios can predict. future stock market returns. The particular set of traditional macroeconomic variables. functioning as predictors of stock returns and the economy, in general, is determined. Thus, the selection of approaches, methods, and indicators. for the analysis and. forecasting of the Russian stock market was carried out according to three criteria: the instability (crises) periods, the information available. for the private investor (generally accepted indicators), and the clarity and ordinariness of analysis and. forecasting methods. A macroeconomic indicator-based approach or an industry-based approach is more often used. for these purposes. Taking into account the instability caused by the economic crises in Russia, the authors combined two approaches. Using traditional linear regression modeling, three out of nine industries and. five out of eight macroeconomic predictors have been. found statistically significant. However, all the models based on these predictors have negative pseudo-R-squared values; therefore, they underperform the historical out-of-sample mean model. It has also been revealed that two out of nine. forecast models, based on significant predictors, provide utility gains. for the mean-variance investor.

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