A maximum likelihood estimator for information precision in the financial market

Abstract

We present a continuous-time model of corporate earnings to study how to estimate the precision of information that investors receive from analyst earnings forecasts about firms' expected earnings growth rates in the real financial world. Based on the model, we develop a maximum likelihood estimator, which is then applied to estimate information precision about the expected earnings growth rate for the S&P 500 index.