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arXiv 1606.05079q-fin.MFmath.OCmath.PR
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部分信息下考虑价格影响的最优清算

Optimal Liquidation under Partial Information with Price Impact

Katia Colaneri, Zehra Eksi, Rüdiger Frey, Michaela Szölgyenyi

摘要:

本文研究了一个市场模型中的最优清算问题,其中买价服从一个几何纯跳跃过程,其局部特征由一个不可观测的有限状态马尔可夫链和清算率驱动。该模型与高频数据的风格化事实一致,例如报价数据的离散性和订单流中的聚集性。我们在分析中包括了暂时性和永久性影响。我们使用随机滤波将最优清算问题转化为完全信息下的等价最优化问题。这导致了分段确定性马尔可夫过程(PDMP)的随机控制问题。我们对这个问题进行了详细的数学分析。特别是,我们推导出的值函数的最优性方程,我们的特征值函数作为连续的粘性解决方案相关联的动态规划方程,我们证明了一个新的比较结果。本文最后用数值结果说明了部分信息和价格对价值函数和最优清算率的影响。

英文摘要:

We study the optimal liquidation problem in a market model where the bid price follows a geometric pure jump process whose local characteristics are driven by an unobservable finite-state Markov chain and by the liquidation rate. This model is consistent with stylized facts of high frequency data such as the discrete nature of tick data and the clustering in the order flow. We include both temporary and permanent effects into our analysis. We use stochastic filtering to reduce the optimal liquidation problem to an equivalent optimization problem under complete information. This leads to a stochastic control problem for piecewise deterministic Markov processes (PDMPs). We carry out a detailed mathematical analysis of this problem. In particular, we derive the optimality equation for the value function, we characterize the value function as continuous viscosity solution of the associated dynamic programming equation, and we prove a novel comparison result. The paper concludes with numerical results illustrating the impact of partial information and price impact on the value function and on the optimal liquidation rate.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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