Decentralized Trading with Private Information
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.
We thank Daron Acemoglu, Fernando Alvarez, Manuel Amador, Abhijit Banerjee, Gadi Barlevy, V.V. Chari, Darrell Duffie, Georgy Egorov, John Geanakoplos, Veronica Guerrieri, Patrick Kehoe, Lasse Pedersen, Dimitri Vayanos, Pierre Olivier Weill, Asher Wolinsky, Pierre Yared and seminar audiences at various universities and conferences for useful comments. We are grateful to our discussants Markus Brunnermeier and Nikolae Garleanu for useful comments and suggestions. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.
Mikhail Golosov & Guido Lorenzoni & Aleh Tsyvinski, 2014. "Decentralized Trading With Private Information," Econometrica, Econometric Society, vol. 82(3), pages 1055-1091, 05. citation courtesy of