Title: A maximum likelihood estimator for information precision in the financial market

Authors: George Li

Addresses: Business School, Finance Department, San Francisco State University, San Francisco, CA 94130, USA

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.

Keywords: information precision; maximum likelihood estimation; MLE; financial markets; continuous time modelling; corporate earnings; earnings forecasting; expected earnings; earnings growth rates; S&P 500.

DOI: 10.1504/IJMEF.2015.072343

International Journal of Monetary Economics and Finance, 2015 Vol.8 No.3, pp.318 - 329

Received: 03 Dec 2014
Accepted: 31 May 2015
Published online: 09 Oct 2015 *

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