Information content of option prices: Comparing analyst forecasts to option-based forecasts

Abstract

The asset pricing literature has been producing increasingly complex and computationally intensive models of stock returns. Separately, professional analysts’ forecast stock returns. Are the sophisticated methods found in the asset pricing literature achieving different forecasts to those of analysts?’ Do the two forecasts’ even capture the same information? In this paper, I hypothesize that analyst forecasts and forecasts constructed using option prices will be different because they place different weights on available information. Using hypothesis tests and quantile regressions, I find that option-based forecasts are statistically significantly different from analyst forecasts at every level of the forecast distribution. Using cross-sectional regressions, I find that the difference originates in the weighting structure of the information sets used to create the forecasts: option-based forecasts incorporate information about the probability of extreme events more heavily while analyst forecasts focus on information about firm and macroeconomic fundamentals.