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Mean-Field Price Formation on Trees with a Network of Relative Performance Concerns

Mean-Field Price Formation on Trees with a Network of Relative Performance Concerns ArXiv ID: 2512.21621 “View on arXiv” Authors: Masaaki Fujii Abstract Financial firms and institutional investors are routinely evaluated based on their performance relative to their peers. These relative performance concerns significantly influence risk-taking behavior and market dynamics. While the literature studying Nash equilibrium under such relative performance competitions is extensive, its effect on asset price formation remains largely unexplored. This paper investigates mean-field equilibrium price formation of a single risky stock in a discrete-time market where agents exhibit exponential utility and relative performance concerns. Unlike existing literature that typically treats asset prices as exogenous, we impose a market-clearing condition to determine the price dynamics endogenously within a relative performance equilibrium. Using a binomial tree framework, we establish the existence and uniqueness of the market-clearing mean-field equilibrium in both single- and multi-population settings. Finally, we provide illustrative numerical examples demonstrating the equilibrium price distributions and agents’ optimal position sizes. ...

December 25, 2025 · 2 min · Research Team

Implied Probabilities and Volatility in Credit Risk: A Merton-Based Approach with Binomial Trees

Implied Probabilities and Volatility in Credit Risk: A Merton-Based Approach with Binomial Trees ArXiv ID: 2506.12694 “View on arXiv” Authors: Jagdish Gnawali, Abootaleb Shirvani, Svetlozar T. Rachev Abstract We explore credit risk pricing by modeling equity as a call option and debt as the difference between the firm’s asset value and a put option, following the structural framework of the Merton model. Our approach proceeds in two stages: first, we calibrate the asset volatility using the Black-Scholes-Merton (BSM) formula; second, we recover implied mean return and probability surfaces under the physical measure. To achieve this, we construct a recombining binomial tree under the real-world (natural) measure, assuming a fixed initial asset value. The volatility input is taken from a specific region of the implied volatility surface - based on moneyness and maturity - which then informs the calibration of drift and probability. A novel mapping is established between risk-neutral and physical parameters, enabling construction of implied surfaces that reflect the market’s credit expectations and offer practical tools for stress testing and credit risk analysis. ...

June 15, 2025 · 2 min · Research Team

A Two-Step Longstaff Schwartz Monte Carlo Approach to Game Option Pricing

A Two-Step Longstaff Schwartz Monte Carlo Approach to Game Option Pricing ArXiv ID: 2401.08093 “View on arXiv” Authors: Unknown Abstract We proposed a two-step Longstaff Schwartz Monte Carlo (LSMC) method with two regression models fitted at each time step to price game options. Although the original LSMC can be used to price game options with an enlarged range of path in regression and a modified cashflow updating rule, we identified a drawback of such approach, which motivated us to propose our approach. We implemented numerical examples with benchmarks using binomial tree and numerical PDE, and it showed that our method produces more reliable results comparing to the original LSMC. ...

January 16, 2024 · 2 min · Research Team