Analysis of Factors Affecting the Risk Premium on the Russian Market

The risk premium study began in 1985, when Mehra and Prescott discovered a discrepancy between US historical data on the risk premium with its theoretical values. So one of the most famous financial puzzles was formed. There were a lot of similar researches after this but no one could solve this puzzle. In order to get closer to the solution, the factors that influenced the award were studied. There are many such works around the world, but there is literally no researches in Russia. For this reason, this work is devoted to the finding and analysis the factors that affect the risk premium in the Russian economy. A 16-years period beginning from 2000 was chosen for this work. The study examines the impact of the following factors: population growth rate, consumer price index (inflation), consumer confidence index, economic freedom index, unemployment rate, exchange rate, export growth, import growth, gross savings as % of GDP, real wage changes from seasonal adjustment, per capita monetary income of the population, Gini coefficient. The research is divided into two specifications: monthly data and annual data. Next, we checked the stationarity of time series (Dickey-Fuller tests) and the explanatory power of the variables (Ramsey test). After this we select the models for each specification that better cover the data imperfections and can explain the impact on the risk premium: linear, ARIMA, ARCH / GARCH. Based on the results of the analysis, the ARCH model was chosen for the first specification, for the second it was a linear, because of the absence of visible imperfections. Significant factors at 5% are: unemployment rate, real wages, consumer confidence index in the category of up to 30 years, population growth rate; at 10%: savings, inflation rate.