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Phases of MANES: Multi-Asset Non-Equilibrium Skew Model of a Strongly Nonlinear Market with Phase Transitions

In: REVIEWS IN MODERN QUANTITATIVE FINANCE

Author

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  • Igor Halperin

Abstract

This chapter presents an analytically tractable and practically oriented model of nonlinear dynamics of a multi-asset market in the limit of a large number of assets. The asset price dynamics are driven by money flows into the market from external investors and their price impact. This leads to a model of a market as an ensemble of interacting nonlinear oscillators with the Langevin dynamics. In a homogeneous portfolio approximation, the mean field treatment of the resulting Langevin dynamics produces the McKean–Vlasov equation as a dynamic equation for market returns. Due to the strong nonlinearity of the McKean–Vlasov equation, the resulting dynamics give rise to ergodicity breaking and first-or second-order phase transitions under variations of model parameters. Using a tractable potential of the Non-Equilibrium Skew (NES) model previously suggested by the author for a single-stock case, the new Multi-Asset NES (MANES) model enables an analytically tractable framework for a multi-asset market. The equilibrium expected market log return is obtained as a self-consistent mean field of the McKean–Vlasov equation and derived in closed form in terms of parameters that are inferred from market prices of S&P 500 index options. The model is able to accurately fit the market data for either benign or distressed market environments, while using only a single volatility parameter.

Suggested Citation

  • Igor Halperin, 2024. "Phases of MANES: Multi-Asset Non-Equilibrium Skew Model of a Strongly Nonlinear Market with Phase Transitions," World Scientific Book Chapters, in: Andrey Itkin (ed.), REVIEWS IN MODERN QUANTITATIVE FINANCE, chapter 2, pages 97-149, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789811281747_0002
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    Keywords

    Quantitative Finance; Financial Engineering; Mathematical Finance; Computational Finance; Computational Methods; Computational Problems; Pricing of Securities; Trading; Market Microstructures; Risk Theory; Queuing Theory; Asset Management Technique; Liability Management Technique; Risk Measures; Solvency; Financial Instability; Fintech; Cryptocurrencies; Financial Machine Learning; Artificial Intelligence; Fintech; Quantum Computing; Distributed Ledgers; Econophysics;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C - Mathematical and Quantitative Methods
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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