Liquidity Factors and Portfolio Optimization in the Russian Stock Market

This research paper is related to the analysis of the liquidity in the Russian stock market, using the daily and high-frequency data at the level of ticks. We conduct the sector analysis that leads to the result that liquidity measures substantially improve the explanatory power of the models for the excess returns for companies from different sectors, and have a positive and significant effect, as investors expect illiquidity and price stocks so that they generate higher expected returns. Furthermore, the conducted Fama Macbeth approach for crisis and post crisis depicts the higher contribution of the liquidity during the crisis period with spread measures outperforming illiquidity measure, while in the post-crisis period the betas become higher. We also apply the Liquidity CAPM framework on the ticks data that leads to higher explanatory power of the models, confirming the importance of taking into account liquidity. The adopted realised spread measure on high frequency data leads to the positive and significant effect of unexpected liquidity. Finally, the research proposes a way of constructing portfolio with the liquidity-weights, enabling to arrive to better risk-adjusted return compared to the standard methods.