Working Paper: NBER ID: w15513
Authors: Mikhail Golosov; Guido Lorenzoni; Aleh Tsyvinski
Abstract: The paper studies asset pricing in informationally decentralized markets. These markets have two key frictions: trading is decentralized (bilateral), and some agents have private information. We analyze how uninformed agents acquire information over time from their bilateral trades. In particular, we show that uninformed agents can learn all the useful information in the long run and that the long-run allocation is Pareto efficient. We then explore how informed agents can exploit their informational advantage in the short run and provide sufficient conditions for the value of information to be positive. Finally, we provide a numerical analysis of the equilibrium trading dynamics and prices.
Keywords: Decentralized Trading; Private Information; Asset Pricing
JEL Codes: D82; D84; G12; G14
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| uninformed agents (D82) | learn all useful information (Y50) |
| learn all useful information (Y50) | equilibrium allocations converge to ex post Pareto efficient allocations (D51) |
| informed agents (D82) | achieve higher utility than uninformed agents (D82) |
| informed agents (D82) | positive value for information (D83) |
| uninformed agents (D82) | learn signals from informed agents (D82) |
| informed agents' marginal rates of substitution (F16) | converge over time (F62) |