What moves stock prices? The role of news, noise, and information

Abstract

We develop a return variance decomposition model to separate the role of different types of information and noise in stock price movements. We disentangle four components: market-wide information, private firm-specific information revealed through trading, firm-specific information revealed through public sources, and noise. Overall, 31% of the return variance is from noise, 37% from public firm-specific information, 24% from private firm-specific information, and 8% from market-wide information. Since the mid-1990s, there has been a dramatic decline in noise and an increase in firm-specific information, consistent with increasing market efficiency.

JEL classification: G12; G14; G15

Keywords: variance decomposition; firm-specific information; market-wide information; stock return synchronicity

Bio

Talis Putnins is a Professor in the Finance Discipline Group at UTS and a member of the Quantitative Finance Research Centre. He has also held positions at the Stockholm School of Economics in Riga and the Baltic International Centre for Economic Policy Studies, and has been a Visiting Scholar at Columbia University and New York University. His main research interests include financial markets, market microstructure, asset pricing, market manipulation, insider trading, and shadow economies. His research has been published in international peer-reviewed journals including the Review of Financial Studies, Journal of Financial Economics, Management Science, Journal of Financial and Quantitative Analysis, Review of Finance, and Experimental Economics. Talis is the recipient of a Discovery Early Career Researcher Award (DECRA) from the Australian Research Council (ARC). Talis has done consulting and policy work for governments, stock exchanges, and financial institutions and served as an expert witness in legal cases.