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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/72129


    Title: 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;Combining Stock Selection Model and Program Trading to Design and Implement an Analyzing Platform. Using Taiwan Stock Data for initial Verification.
    Authors: 黃天蔚;Huang,Tien-Wei
    Contributors: 資訊管理學系
    Keywords: 選股模型;程式交易;量化投資;選股結合選時;Stock Selection Model;Programing Trading;Fundamental Analysis;Technical Analysis
    Date: 2016-07-14
    Issue Date: 2016-10-13 14:27:29 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 由於股票市場的發展,如何預測股票價格未來變動趨勢早已成為每個證券投資人最關心的課題,然而股票市場是十分複雜且龐大的系統,有許多專家提出了各種不同基本分析與技術分析的理論與方法,且因計算機工具的蓬勃發展,讓許多專家得以更方便快速的於兩大分析領域中使用量化的分析方式進行分析。雖然對此兩大領域之量化分析平台或系統的發展皆已非常成熟,但台灣市面上之系統有其使用限制,如:CMoney法人投資決策系統無法自行撰寫交易策略、無法採用較複雜的資金配置;Multicharts不提供基本面因子給使用者參考,且台灣市面上尚無功能完善之結合選股與程式交易之系統或平台,功能完善之系統應具備讓使用者自由選用基本面因子搭配自行撰寫的交易策略再結合資金配置方法進而進行回測分析。
    故本研究參考國內、外與基本面選股回測績效分析之相關研究內容,並參考「CMoney法人投資決策支援系統」之基本面選股回測程式運算邏輯,以量化之方式針對如何實作結合選股與程式交易之系統平台進行探討,於本研究中提出「基本面選股」、「選股定時進出回測績效分析」、「選股結合程式交易選時回測績效分析」,三大程式運算流程以及資料庫儲存邏輯,並採用資料庫技術與系統整合技術將上述三大功能完整實作。最後採用台灣經濟新報財經資料庫做為資料來源,以台灣股票市場為目標市場,2008年5月1日至2015年12月31日之台灣上市櫃股票(不包含下市)作為樣本,針對本研究之系統進行回測績效結果驗證以及系統執行步驟驗證。且於本系統選股定時進出以及選股結合程式交易選時之回測績效結果分別為年化報酬率 17 %、年化報酬率38.2 %。
    ;Since the development of the stock market, predict changes in the stock price has became most concerned issue. However, stock market is very complex system, many experts have proposed various theories which can used to predict stock price such as fundamental analysis and technical analysis. Although the development of quantitative analysis platform for fundamental analysis or technical analysis has come of age. But there are still have many defects. For example, investment decision support system which developed by CMoney is very useful to do stock market analysis but can not let user create trading strategy or use more complex capital allocation method in analysis. And Multicharts which is a kind of program trading platform do not provide financial indicators to help user to make decision.
    Therefore, this research refer previous researchs which topic is about stock fundamentals backtesting performance analysis and the program logic of investment decision support system, and then implement an analyzing platform which combining stock selection model and program trading let user can use this analyzing platform to do backtesting and doing data mining.
    The purpose of this study is to provide three functions. 1. According to financial indicators to do stock selection. 2. Buy and hold backtesting analysis. 3. Market timing backtesting analysis. Using Taiwan stock data for initial verification, and get good results with irr 17 % and irr 38.2 % in 2. and 3. functional verification.
    Appears in Collections:[資訊管理研究所] 博碩士論文

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