Price Formation in Financial Markets: A Mean-Field Game Perspective
A new book chapter presents a mean-field game model to explain how asset prices form in markets with limited liquidity and order book trading. The authors derive an analytical formula linking prices to order flow, revealing that liquidity constraints can push prices away from expected values. Using high-frequency data from ten NASDAQ stocks, the model captures real market effects and shows liquidity can amplify price swings. The chapter suggests further discussion on practical applications is needed.
What it examines
This chapter introduces a mean-field game model to explain how asset prices are formed in financial markets using order books, considering the effects of limited liquidity. The authors provide an analytical formula for price and test their model with high-frequency trading data from ten NASDAQ stocks.
What it concludes
The results show that the model accurately captures price formation under liquidity constraints. These findings can help improve trading strategies, risk management, and market design. Future research may extend the model to other markets or include more complex trading behaviors for deeper insights.
Evidence objects
A groundbreaking mean-field game model links asset prices to order flow, offering a fresh perspective on how market dynamics and liquidity costs shape prices in financial markets with limited liquidity.
key_findings bullet 1 · key_findings · validation V0
Massive numerical experiments using high-frequency NASDAQ data validate the model, revealing surprising trends: liquidity constraints can amplify price movements and cause prices to deviate from expected values.
key_findings bullet 2 · key_findings · validation V0
While the model is robust and combines advanced mathematics with real-world data, the chapter leaves unanswered questions about practical implementation and lacks a deeper discussion of its limitations and real-world applications.
key_findings bullet 3 · key_findings · validation V0
This paper introduces a novel mean-field game model for limit order book price formation, uniquely incorporating liquidity costs and deriving an analytical price formula based on realized order flow. Its originality lies in applying mean-field games to LOBs, validated with high-frequency NASDAQ data, offering significant insights for market microstructure research.
key_findings bullet 4 · key_findings · validation V0
Raw abstract and provenance
- We propose a mean-field game model to study the price formation of an asset negotiated in an order book, considering costs stemming from limited liquidity. We derive an …
Source row: 1595 · abstract type: snippet