Liquidity and Market Microstructure Noise: Evidence from the Pekao Data

Abstract

The availability of ultra-high frequency data justifies the use of a continuous-time approach in stock prices modeling. However, this data contain, apart from the information about the price process, a microstructure noise causing a bias in the realized volatility. This noise is connected with all the reality of trade. In the paper we separate the microstructure noise from the price process and determine the noise to signal ratio for the estimates of the realized volatility in the case of the shares of the Polish company Pekao S.A. The results are used to discover the optimal sampling frequency for the realized volatility calculation. Moreover, we check the linkages between the noise and some liquidity measures.