双向网格约束随机过程的收缩和收缩

A. Taranto, Shahjahan Khan
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引用次数: 4

摘要

网格交易问题(GTP)应用于投资组合损失最小化、广义动态套期保值和算法交易中,研究了离散随机漫步和Ito扩散对双向网格约束(BGC)随机过程中利润Pt和权益E_t随时间变化的影响。推导并证明了GTP的综合离散差分方程(DDE)和连续随机微分方程(SDE)。这使得基金经理和交易员能够更好地对波动性的影响进行压力测试,以降低风险并产生正回报。然后对这些定理进行模拟,用图表来补充理论模型。本研究不仅扩展了一个丰富的数学问题,它本身就可以进一步研究,而且还将其应用扩展到上述金融领域。
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Drawdown and Drawup of Bi-Directional Grid Constrained Stochastic Processes
The Grid Trading Problem (GTP) of mathematical finance, used in portfolio loss minimization, generalized dynamic hedging and algorithmic trading, is researched by examining the impact of the drawdown and drawup of discrete random walks and of Ito diffusions on the Bi-Directional Grid Constrained (BGC) stochastic process for profit Pt and equity E_t over time. A comprehensive Discrete Difference Equation (DDE) and a continuous Stochastic Differential Equation (SDE) are derived and proved for the GTP. This allows fund managers and traders the ability to better stress test the impact of volatility to reduce risk and generate positive returns. These theorems are then simulated to complement the theoretical models with charts. Not only does this research extend a rich mathematical problem that can be further researched in its own right, but it also extends the applications into the above areas of finance.
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33.30%
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