论文标题
资产投资组合的多维随机Stefan财务模型
The multi-dimensional Stochastic Stefan Financial Model for a portfolio of assets
论文作者
论文摘要
提出的财务模型涉及通过卖出或(和)以波动性购买订单的$ n $资产投资组合的清算过程。我们在财务环境中介绍了该模型的严格数学公式,从而导致噪声带来$ n $维的外部抛物线stefan问题。特别是,我们的目的是在短时间内估算零交易的领域,其直径约为投资组合资产的最小值,分别从每个资产的$ n $限制订单账簿中的订单中的订单中的最低差价。在尺寸$ n = 3 $中,对于零波动率,此问题是Ostwald成熟的平均野外模型,并已由Niethammer提出和分析。在其中,当初始移动边界由分离良好的球体组成时,对于接口的动力学和溶液的渐近分布,ODE的一阶近似系统是严格得出的。在我们的财务案例中,我们提出了一个球形移动边界方法,其中零交易区域由以投资组合各种价格组合的球形域组成,而每个领域可能与不同的市场相对应;相关的半径代表最小扩散的一半。我们应用ITôCilculus,并为随机版本动力学提供二阶形式渐近学,该动力学是作为随时间进化的随机微分方程系统编写的。第二阶近似似乎使财务模型与交易密度的大扩散假设断开。此外,我们通过数值求解近似系统。
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 Itô 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.