论文标题
两体财务经销商模型的精确解决方案:从动力学理论的角度重新审视
Exact solution to two-body financial dealer model: revisited from the viewpoint of kinetic theory
论文作者
论文摘要
重新审视了两体随机经销商模型,以使用动力学方法为平均订单书概况提供精确的解决方案。经销商模型是一个微观财务模型,单个交易者随机地对极限订单的价格做出决定,然后就交易达成协议。在文献中,该模型在几种情况下得到了解决:两体交易者的精确解决方案$ n = 2 $,对于许多交易者$ n \ gg 1 $的平均解决方案。值得注意的是,尽管动力学理论在$ n \ gg 1 $的平均场分析中起着重要作用,但对于$ n = 2 $的情况,其作用仍然难以捉摸。在本文中,我们重新审视了两体经销商模型$ n = 2 $,以阐明动力学理论的实用性。我们首先通过几种方法来得出两体经销商模型的确切主liouville方程。接下来,我们从概率电流的角度说明了主liouville方程的物理图片。然后,精确地求解了主liouville方程,以得出订单簿配置文件和平均交易间隔。此外,我们通过通过市场中间值结合交易者之间的相互作用并在动力学框架中恰好解决该模型,从而引入了广义的两体经销商模型。我们最终通过数值模拟确认了我们的精确解决方案。这项工作通过开发更好的数学直觉为生态物理学模型提供了系统的数学基础。
The two-body stochastic dealer model is revisited to provide an exact solution to the average order-book profile using the kinetic approach. The dealer model is a microscopic financial model where individual traders make decisions on limit-order prices stochastically and then reach agreements on transactions. In the literature, this model was solved for several cases: an exact solution for two-body traders $N=2$ and a mean-field solution for many traders $N\gg 1$. Remarkably, while kinetic theory plays a significant role in the mean-field analysis for $N\gg 1$, its role is still elusive for the case of $N=2$. In this paper, we revisit the two-body dealer model $N=2$ to clarify the utility of the kinetic theory. We first derive the exact master-Liouville equations for the two-body dealer model by several methods. We next illustrate the physical picture of the master-Liouville equation from the viewpoint of the probability currents. The master-Liouville equations are then solved exactly to derive the order-book profile and the average transaction interval. Furthermore, we introduce a generalised two-body dealer model by incorporating interaction between traders via the market midprice and exactly solve the model within the kinetic framework. We finally confirm our exact solution by numerical simulations. This work provides a systematic mathematical basis for the econophysics model by developing better mathematical intuition.