Explaining the Idiosyncratic Volatility Puzzle With a Bayesian-Updating Model
69 Pages Posted: 7 May 2020
Date Written: April 13, 2020
We find that the idiosyncratic volatility (IVOL) puzzle exists only among firms that under-perform their benchmark or release negative earnings surprises. We explain the findings using a Bayesian updating model in which agents observe noisy signals about future cash flows. In this setting, high IVOL increases the likelihood of observing earnings surprises. When the noisy surprise is negative, returns exhibit a negative momentum, and the IVOL puzzle emerges. When controlling for relative performance and signal precision, the IVOL puzzle disappears. Our explanation alone can account for up to 75% of the IVOL puzzle, which is more than all other existing theories combined.
Keywords: Idiosyncratic Volatility Puzzle, Bayesian Updating, Signal Precision
JEL Classification: G12, G14
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