Incomplete Information and the Liquidity Premium Puzzle
56 Pages Posted: 14 Dec 2018
Date Written: October 10, 2018
We examine the problem of an investor who trades in a market with unobservable regime shifts. The investor learns from past prices and is subject to transaction costs. We obtain liquidity premia that are 75% larger compared to a benchmark model with observable market shifts. The large premia in our model are driven primarily by suboptimal risk exposure, because turnover is low under incomplete information. In contrast, the benchmark model produces (mechanically) high turnover and heavy trading costs. We provide empirical support for our model using the dispersion in analyst forecasts as a proxy for incomplete information. Overall, our results can help explain the large disconnect between theory and evidence regarding the magnitude of liquidity premia, which has been a longstanding puzzle in the literature.
Keywords: Regime Shifts, Incomplete Information, Transaction Costs, Liquidity Premia
JEL Classification: C61, D11, D91, G11
Suggested Citation: Suggested Citation