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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/72126


    Title: 結合程式交易與選股模型的分析平台之設計與實作 – 以美國股票市場為例;Combining Program Trading and Stock Selection Model to Design and Implement an Analyzing Platform. Using American Stock Data for initial Verification.
    Authors: 彭康哲;Peng,Kang-Jhe
    Contributors: 資訊管理學系
    Keywords: 技術分析;程式交易;選股模型;基本面分析;選時選股整合模型;Technical Analysis;Program Trading;Stock Selection Model;Fundamental Analysis;Integrated Model of Market Timing Model and Stock Selection Model
    Date: 2016-07-14
    Issue Date: 2016-10-13 14:27:19 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 股市投資屬於一種高風險高報酬的投資方式,其已成為民眾投資方法中不可或缺的一部份,有大量學者專注於股市的基本面分析以及技術分析之相關研究,期望於股市投資中能帶來更穩定與更高額的報酬效益。
    在實際交易時,投資者會受到許多因素影響投資決策,造成投資獲利不佳或不穩定。因此,部分投資人將交易轉介於電腦程式進行買賣。程式交易是以明確的程式語言定義金融商品之買賣條件,並交付於電腦自動執行交易,可避免人為因素所造成的投資問題。
    美國標準普爾公司(Standard & Poor)資深分析師Richard Tortoriello於2009年出版一書 “Quantitative Strategies for Achieving Alpha”,其採用量化投資的方式全面分析美國股票市場。Tortoriello選股模型依照基本面因子之特性進行排序,於每年度切割出不同的投資組合,並根據選股模型的結果,以量化的方式進行股市交易。但一般投資者無充足資源可依此選股模型進行交易:第一、購買一種投資組合須持有近400支股票;第二、持有投資組合需數年之久。
    本研究以此模型為出發點,與黃天蔚(2016)之研究「結合選股模型與程式交易的分析平台之設計與實作 – 以台灣股票市場為例」相互輔助分析平台之設計與實作,旨在整合各項市售軟體,使用MultiCharts與SQL Server實現Tortoriello選股模型,本研究以美國股市資料作為系統之可用性驗證。此外本研究提出一選時選股模型,藉由程式交易軟體試圖找出交易進出點訊號,試圖縮小投資人投資組合的個股數目。
    以往鮮少研究嘗試用建立平台的方式在程式交易中加入基本面因子作為交易邏輯,並以量化的方式研究結合技術分析與基本面分析之交易績效表現。所以,本研究的第二個貢獻為撰寫DLL應用於MultiCharts之交易策略中,使交易策略得以使用基本面因子撰寫各式各樣的交易邏輯,並以Portfolio Trader以量化的方式進行大量商品回測。系統以美國股市資料作為驗證。本研究將最佳化流程拆解為兩細部流程,將指數複雜度之問題降至多項式複雜度。
    本研究最後在交易策略中加入自由現金流/價格作濾網進行回測,並以此作為單因子選股模型進行系統驗證。相較於Tortoriello選股模型之第一分位,結合程式交易之選時選股模型的複合平均投資報酬率有29.5%的提升。實驗結果顯示本研究系統之可執行性,並可實現Tortoriello選股模型與計算選時選股模型的交易績效。;Stock investment is a high risk, high reward investment behavior. It is the main method of investments. There are many study focused on fundamental analysis and technical analysis in stock market. They hope to find the investment model which is more stable and make more excess returns.
    In actual trading situation, investment decisions of investors will be influenced by many factors. This situation make investment to be worthless and much unstable. Therefore, many investors are turn to using program trading. Program trading use program languages to define the conditions of buying and selling products and execute trading automatically. This can avoid problems caused by human investment.
    Richard Tortoriello, who was senior analyst in Standard & Poor, published the book “Quantitative Strategies for Achieving Alpha” in 2009. This book described a quantitative investment method to analyze the whole American stock market. Tortoriello’s stock selection model use fundamental factors to rank companies, and divided them into 5 parts each year. Each part is one portfolio. It buy and hold portfolio every year. Finally, Tortoriello compare the trading performance of every stock selection model. This book analyze the correlation between fundamental factors and trading performance. Generally, investors have no enough resources to trade according to Tortoriello’s stock selection model. First, there are almost four hundreds stocks need to hold in one portfolio in each year. Second, investors need to hold these portfolios in many years.
    This study cooperate with Ryan Huang’s study “Combining Stock Selection Model and Program Trading to Design and Implement an Analyzing Platform. Using Taiwan Stock Data for initial Verification” to design and implement an analyzing platform based on Tortoriello’s stock selection model. The purpose of this study is combing commercial software, including MultiCharts and SQL Server, to implement the platform integrated market timing model and stock selection model. This study use American stock data for initial verification of analyzing platform. Besides, this study combine the factor of program trading into Tortoriello’s stock selection model, and try to cut down the number of stocks need to hold in portfolio of Tortoriello’s stock selection model.
    There were few study experiment the trading performance about using fundamental factors into trading strategy, and use quantitative investment method to compute its trading performance in the past. Therefore, second contribution of this study is to program two DLLs and execute them in MultiCharts. These DLLs let MultiCharts can run the trading strategy which is using fundamental factors. This study use Portfolio Trader to execute quantitatively back testing. This will use American stock data for system verification. Otherwise, this study divide the optimization process of trading strategy into two parts. This two detail process translate the exponent complexity of optimization process into polynomial complexity of optimization process.
    This study use “free cash flow to price” to initial verify this analyzing platform. Compare to Tortoriello’s stock selection model, the trading performance of integrated model of market timing model and stock selection model is higher 29.5% than the trading performance of Tortoriello’s stock selection model. The result of experiment shows that an analyzing platform developed by this study can calculate the performance of stock selection model, and can implement Tortoriello’s stock selection model and integrated model of market timing model and stock selection model.
    Appears in Collections:[資訊管理研究所] 博碩士論文

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