Abstract We present an equilibrium model of dynamic trading, learning, and pricing by strategic investors with trading targets and price impact. Since trading targets are private, investors filter the child order flow dynamically over time to estimate the latent underlying parent trading demand imbalance and to forecast its impact on subsequent price-pressure dynamics. We prove existence of an equilibrium and solve for equilibrium trading strategies and prices as the solution to a system of coupled ODEs. Trading strategies are combinations of trading towards investor targets, liquidity provision for other investors’ demands, and speculation based on learning about latent underlying trading-demand imbalances.
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Price Setting With Strategic Complementarities as a Mean Field Game
We study the propagation of monetary shocks in a sticky‐price general equilibrium economy where the firms' pricing strategy features a complementarity with the decisions of other firms. In a dynamic equilibrium, the firm's price‐setting decisions depend on aggregates, which in turn depend on the firms' decisions. We cast this fixed‐point problem as a Mean Field Game and prove several analytic results. We establish existence and uniqueness of the equilibrium and characterize the impulse response function (IRF) of output following an aggregate shock. We prove that strategic complementarities make the IRF larger at each horizon. We establish that complementarities may give rise to an IRF with a hump‐shaped profile. As the complementarity becomes large enough, the IRF diverges, and at a critical point there is no equilibrium. Finally, we show that the amplification effect of the strategic interactions is similar across models: the Calvo model and the Golosov–Lucas model display a comparable amplification, in spite of the fact that the non‐neutrality in Calvo is much larger.
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- Award ID(s):
- 2153822
- PAR ID:
- 10541746
- Publisher / Repository:
- Wiley Online Library
- Date Published:
- Journal Name:
- Econometrica
- Volume:
- 91
- Issue:
- 6
- ISSN:
- 0012-9682
- Page Range / eLocation ID:
- 2005 to 2039
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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