英文标题：
《Mathematical Foundations of Realtime Equity Trading. Liquidity Deficit
  and Market Dynamics. Automated Trading Machines》
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作者：
Vladislav Gennadievich Malyshkin and Ray Bakhramov
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最新提交年份：
2016
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英文摘要：
  We postulates, and then show experimentally, that liquidity deficit is the driving force of the markets. In the first part of the paper a kinematic of liquidity deficit is developed. The calculus-like approach, which is based on Radon--Nikodym derivatives and their generalization, allows us to calculate important characteristics of observable market dynamics. In the second part of the paper this calculus is used in an attempt to build a dynamic equation in the form: future price tend to the value maximizing the number of shares traded per unit time. To build a practical automated trading machine P&L dynamics instead of price dynamics is considered. This allows a trading automate resilient to catastrophic P&L drains to be built. The results are very promising, yet when all the fees and trading commissions are taken into account, are close to breakeven. In the end of the paper important criteria for automated trading systems are presented. We list the system types that can and cannot make money on the market. These criteria can be successfully applied not only by automated trading machines, but also by a human trader.
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中文摘要：
我们假设，然后通过实验证明，流动性赤字是市场的驱动力。本文第一部分对流动性赤字进行了运动学分析。基于Radon-Nikodym导数及其推广的类似微积分的方法，允许我们计算可观测市场动态的重要特征。在论文的第二部分中，该演算用于尝试建立一个动态方程，其形式为：未来价格趋向于单位时间内交易的股票数量最大化的价值。为了建立一个实用的自动交易机，需要考虑损益动态而不是价格动态。这使得交易系统能够应对灾难性的损益流失。结果是非常有希望的，但是当考虑到所有的费用和交易佣金时，已经接近收支平衡。本文最后介绍了自动交易系统的重要标准。我们列出了能够和不能在市场上赚钱的系统类型。这些标准不仅可以被自动交易机成功应用，也可以被人类交易员成功应用。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Computational Finance        计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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