Noisy information and stock market returns

Purpose - This paper aims to study whether noisy public information that investors receive about the expected aggregate dividend growth rate can help better understand the large average equity premium and stock return volatility in the US financial market. Design/methodology/approach - This paper considers a dynamic asset pricing model with a representative agent, who cannot observe the expected growth rate of dividends and must learn its value by using noisy information. In addition, this paper presents a simple model for noisy information calibration. Findings - With a coefficient of relative risk aversion below 10 and the time impatience parameter between 0 and 1, the calibrated model is able to yield an average risk-free interest rate, equity premium and stock return volatility that are close to the stylized facts in the US financial market. Originality/value - First, this paper presents a different equilibrium model with a simple “catching up with the Joneses” preference and noisy information. Second, this paper develops a simple calibration procedure to calibrate the information process to study whether the calibrated model can help explain the large average equity premium and stock return volatility in the US financial market data.