Market Depth and Noisy Prices: A Maximum Likelihood Approach

The information content of high frequency data has made them the main instruments for studying market microstructure. However, the noise content of this data may negatively affect the results of studies on market microstructure. Using maximum likelihood methodology, we disentangle from high frequency observations on the transaction prices of a sample of Tehran Stock Exchange stocks a fundamental component and a microstructure noise component. We then relate these statistical measurements of market microstructure noise to different financial measures of their market depth. We find that stocks with higher market depth have higher noise measured from their high frequency returns. This is in accordance with Fischer Black’s hypothesis that the existence of noise traders and the noise, which can be caused by the activities of this group of traders, to be the vital condition of a liquid market. We also find that pre-trade depth measures are the most powerful depth measure in explaining the noise in the market.