英文标题:
《Dynamical Models of Stock Prices Based on Technical Trading Rules Part
III: Application to Hong Kong Stocks》
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作者:
Li-Xin Wang
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最新提交年份:
2016
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英文摘要:
In Part III of this study, we apply the price dynamical model with big buyers and big sellers developed in Part I of this paper to the daily closing prices of the top 20 banking and real estate stocks listed in the Hong Kong Stock Exchange. The basic idea is to estimate the strength parameters of the big buyers and the big sellers in the model and make buy/sell decisions based on these parameter estimates. We propose two trading strategies: (i) Follow-the-Big-Buyer which buys when big buyer begins to appear and there is no sign of big sellers, holds the stock as long as the big buyer is still there, and sells the stock once the big buyer disappears; and (ii) Ride-the-Mood which buys as soon as the big buyer strength begins to surpass the big seller strength, and sells the stock once the opposite happens. Based on the testing over 245 two-year intervals uniformly distributed across the seven years from 03-July-2007 to 02-July-2014 which includes a variety of scenarios, the net profits would increase 67% or 120% on average if an investor switched from the benchmark Buy-and-Hold strategy to the Follow-the-Big-Buyer or Ride-the-Mood strategies during this period, respectively.
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中文摘要:
在本研究的第三部分,我们将本文第一部分开发的大买家和大卖家价格动态模型应用于香港证券交易所上市的前20家银行和房地产股票的每日收盘价。其基本思想是估计模型中大买家和大卖家的实力参数,并根据这些参数估计做出买入/卖出决策。我们提出了两种交易策略:(i)跟随大买家,当大买家开始出现且没有大卖家的迹象时买入,只要大买家还在,就持有股票,一旦大买家消失,就卖出股票;(ii)一旦大买家的实力开始超过大卖家的实力,就立即买入,一旦相反的情况发生,就卖出股票。根据2007年7月3日至2014年7月2日这七年中245个两年期的测试,包括各种情景,如果投资者在此期间分别从基准买入并持有策略转向跟随大买家或乘坐情绪策略,净利润将平均增长67%或120%。
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Trading and Market Microstructure 交易与市场微观结构
分类描述:Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构,流动性,交易和拍卖设计,自动化交易,基于代理的建模和做市
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一级分类:Computer Science 计算机科学
二级分类:Computational Engineering, Finance, and Science 计算工程、金融和科学
分类描述:Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的,集中在技术和工具,使挑战性的计算模拟能够执行,其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4(经济学)中的材料。
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一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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