Optimal Bubble Riding: A Mean Field Game with Varying Entry Times
Ludovic Tangpi, Shichun Wang

TL;DR
This paper develops a mean field game model for optimal liquidation during financial bubbles, accounting for varying entry times of traders and both endogenous and exogenous market crashes, with theoretical and numerical analysis.
Contribution
It introduces a novel mean field game framework with varying entry times and incorporates exogenous crash times using progressive enlargement of filtrations.
Findings
Equilibrium strategies decompose into pre- and post-burst segments.
Existence of MFG equilibria proved in a generalized setting.
Numerical simulations reveal relationships between bubble bursts and trader strategies.
Abstract
Recent financial bubbles such as the emergence of cryptocurrencies and "meme stocks" have gained increasing attention from both retail and institutional investors. In this paper, we propose a game-theoretic model on optimal liquidation in the presence of an asset bubble. Our setup allows the influx of players to fuel the price of the asset. Moreover, traders will enter the market at possibly different times and take advantage of the uptrend at the risk of an inevitable crash. In particular, we consider two types of crashes: an endogenous burst which results from excessive selling, and an exogenous burst which cannot be anticipated and is independent from the actions of the traders. The popularity of asset bubbles suggests a large-population setting, which naturally leads to a mean field game (MFG) formulation. We introduce a class of MFGs with varying entry times. In particular, an…
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Taxonomy
TopicsFinancial Markets and Investment Strategies · Complex Systems and Time Series Analysis · Economic theories and models
