交易员通常在处理大单交易时会遇到困难，因为市场没有足够的流动性来消化这些买单或卖单。交易员想要在对市场产生冲击最小的情况下完成加仓或平仓，或者他们想设计一套程序来达成这个目的。 / 由于每次的交易结果都是一个随机变量，为了方便比较，我们可以设置一个比较基准，在本文中我们选用。 / 本文对之前存在的动态一致性风险测度模型的一大改进是引入了动量效应。在短时的股市中动量效应就有明显效应。 / 我们的最优策略是当市场朝我们不利的方向变动时我们加速仓位的增加或减少，而朝我们有利的方向变动时我们减缓我们的动作。我们的最优策略每期都会出请或买入一个预先设定的比例的股票，同时我们会在交易的初期加快我们的买卖处理，而在后期放缓动作。 / 我们的最优策略是时间一致的，并且是一个动态变化的策略。 / For an equity trader, one problem he faces is to execute large order of stocks for his clients. The trader seeks to optimize his performance for buying and selling stocks. Basically various costs incurred during the trading includes the commission fees, margin loans, bid-ask spread, price impacts, taxes and other occasional costs. But among the all, the price impact takes the largest part. / In a sell program, the implementation shortfall is the differience between the value of the trader’s initial equity position and the sum of the cash flow he receives from his trading process. Because of the randomness inherited in the stock price process, the resulting implementation shortfall is a random variable, and we should project the random variable into real number to compare. The measure we choose is the dynamic coherent risk measure. / One of the most significant improvements of our model is the inclusion of momentum effect. Momentum is a significant effect when considering stock price dynamics in a daily circle. Another main contribution is the approximation method used in solving our model, which helps reduce much computation burden. / Our strategy applies best to the high frequency trading problem due to the nature of our approximation method. The optimal strategy in our framework is to trade more when the current price drift is negative. This is mainly due to the prevention from future possible negative price drifts. Our strategy also shows that, in addition to liquidate a fixed proportion of inventory at each period, the trader has to trade faster at earlier periods.Our optimal strategy derived from dynamic programming is time consistent and is an adapted process. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / He, Mengfei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 132-134). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.10 / Chapter 2.1 --- Model Comparison --- p.10 / Chapter 2.1.1 --- Price dynamics --- p.10 / Chapter 2.1.2 --- Price impacts --- p.11 / Chapter 2.1.3 --- Inventory constraints --- p.14 / Chapter 2.1.4 --- Objective functions and risk measures --- p.15 / Chapter 2.1.5 --- Discrete or continuous framework --- p.17 / Chapter 2.2 --- Work by Bertsimas and Lo --- p.18 / Chapter 2.2.1 --- Formulation under Linear Price Impact --- p.21 / Chapter 2.2.2 --- Formulation under LPT Law --- p.22 / Chapter 2.2.3 --- Formulation under General Price Impact --- p.26 / Chapter 2.2.4 --- Portfolio Case --- p.28 / Chapter 2.3 --- A Series ofWorks by Almgren --- p.29 / Chapter 2.3.1 --- Adaptive Arrival Price --- p.29 / Chapter 2.3.2 --- Bayesian Adaptive Trading with a Daily Cycle --- p.32 / Chapter 2.3.3 --- Mean-Variance Optimal Adaptive Execution --- p.36 / Chapter 2.4 --- Work by Lin and Pena --- p.42 / Chapter 2.4.1 --- Multiple Assets --- p.46 / Chapter 2.5 --- A Series ofWorks by Forsyth --- p.48 / Chapter 2.5.1 --- A Hamilton-Jacobi-Bellman Approach to Optimal Trade Execution --- p.49 / Chapter 2.5.2 --- A Mean Quadratic Variation Approach --- p.55 / Chapter 2.6 --- A Series ofWorks by Schied --- p.58 / Chapter 2.6.1 --- Optimal Trade Execution in Limit Order BookModels --- p.58 / Chapter 2.6.2 --- Optimal Trade Execution under Geometric BrownianMotion --- p.66 / Chapter 2.7 --- Work byMoazeni --- p.69 / Chapter 3 --- Model Setting --- p.71 / Chapter 3.1 --- ExecutionModel --- p.71 / Chapter 3.2 --- Coherent Dynamic RiskMeasures --- p.81 / Chapter 3.3 --- Optimization Formulation --- p.84 / Chapter 4 --- Solution Methodologies --- p.89 / Chapter 4.1 --- BinomialModel --- p.89 / Chapter 4.2 --- Linear Approximation --- p.92 / Chapter 4.3 --- Numerical Results --- p.107 / Chapter 4.4 --- Simulation Results --- p.110 / Chapter 4.5 --- Efficient Frontier --- p.111 / Chapter 4.6 --- CVaR Case --- p.113 / Chapter 5 --- Conclusions and Future Research --- p.119 / Chapter 5.1 --- Conclusions --- p.119 / Chapter 5.2 --- Future Research --- p.121 / Chapter A --- Equation Derivation --- p.124 / Bibliography --- p.132
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328770 |
| Date | January 2013 |
| Contributors | He, Mengfei., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | electronic resource, electronic resource, remote, 1 online resource (xiv, 134 leaves) : ill. (some col.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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