The multi-dimensional Stochastic Stefan Financial Model for a portfolio of assets

TL;DR

This paper introduces a multi-dimensional stochastic Stefan model for asset portfolios, analyzing zero trading zones and their dynamics using mathematical and numerical methods, extending mean field models to financial markets.

Contribution

It formulates a novel stochastic Stefan problem for portfolios, incorporating noise and zero trading zones, with a spherical boundary approach and second order asymptotics.

Findings

Derived second order asymptotics for stochastic radii evolution.

Numerically solved the approximating stochastic differential equations.

Proposed a spherical boundary model for zero trading areas.

Abstract

The financial model proposed involves the liquidation process of a portfolio of $n$ assets through sell or (and) buy orders with volatility. We present the rigorous mathematical formulation of this model in a financial setting resulting to an $n$-dimensional outer parabolic Stefan problem with noise. In particular, our aim is to estimate for a short time period the areas of zero trading, and their diameter which approximates the minimum of the $n$ spreads of the portfolio assets for orders from the $n$ limit order books of each asset respectively. In dimensions $n=3$, and for zero volatility, this problem stands as a mean field model for Ostwald ripening, and has been proposed and analyzed by Niethammer. Therein, when the initial moving boundary consists of well separated spheres, a first order approximation system of odes had been rigorously derived for the dynamics of the interfaces and the asymptotic profile of the solution. In our financial case, we propose a spherical moving boundaries approach where the zero trading area consists of a union of spherical domains centered at portfolios various prices, while each sphere may correspond to a different market; the relevant radii represent the half of the minimum spread. We apply It\^o calculus and provide second order formal asymptotics for the stochastic version dynamics, written as a system of stochastic differential equations for the radii evolution in time. A second order approximation seems to disconnect the financial model from the large diffusion assumption for the trading density. Moreover, we solve the approximating systems numerically.