運用等分法與核心交易策略建構投資組合之自動化交易分析平台—以美股為範例;An Automatic Trading Analyze Platform for Portfolio which Construct from Equal Divided Method and Trading Strategy on America Stock Market

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/81169

Title:	運用等分法與核心交易策略建構投資組合之自動化交易分析平台—以美股為範例;An Automatic Trading Analyze Platform for Portfolio which Construct from Equal Divided Method and Trading Strategy on America Stock Market
Authors:	張維真;Chang, Weichen
Contributors:	資訊管理學系
Keywords:	程式交易;基本面與技術面分析;自動客製化平台;可擴充投資組合;Program Trading;Technical and Fundamental Analysis;Automatic Customized Platform;Scalable Portfolio
Date:	2019-06-21
Issue Date:	2019-09-03 15:37:57 (UTC+8)
Publisher:	國立中央大學
Abstract:	金融科技的興盛帶來一波創新金融服務，其中如何運用程式交易結合股票基本面進行分析也是大眾關心的議題，然而目前尚未有完整的系統能達成自動針對多種基本面與程式交易綜合運用做出好的回測功能，至於股票交易必備的多投資組合分析功能，更是付之闕如。因此本論文參考謝昀峻（2018）之研究，以等分法及技術面策略進行交易分析，並重構其原有架構，建置一個（1）「可擴充程式交易回測結構」，（2）結合基本面與技術面分析方法，且（3）能夠在不同股票市場進行多策略、多商品投資組合績效回測，並（4）用視覺化方式呈現績效分析結果的平台，提供使用者以更簡便的方式進行股票投資組合分析與評估。本研究利用Amiboker、Python、MySQL、Jupyter Notebook以及Plotly進行實作，研究1998年1月1日至2016年12月31日於紐約證券交易所上市之股票，將投資組合參數物件導向化，參數包含技術面交易策略及其參數設定、資金配置法、資金再投入法、基本面因子及其排名、與最大持有股數，連結Python程式設計與程式交易軟體Amibroker，使回測與分析成為一套完整流程，能夠客製化使用者欲分析之股票與參數設定，並以圖表清楚展現分析結果。經過驗證後本研究發現，有些價格動量面因子排名與獲利間有高度相關性，且在第一排名中能夠有高獲利，CAGR約可達到40%，表示我們在選擇投資標的時，可參考這些基本面因子及其他投資組合參數設定，以獲得更高的報酬。 ;The development of financial technology helps financial services growing up. How to combine program trading and fundamental analysis is always an issue in public. However, there isn′t a complete system for automatic back testing on several fundamental factors with program trading. Also lack of multi-portfolio analysis method. Yun-Chun, Hsieh (2018) has pointed out that using equal divided method based on fundamental factors to analyze stock selection will indeed have greater benefits. This study reconstructs that research to build a scalable portfolio structure, integrate technical and fundamental analysis, back test the performance of multi-portfolio and multi-stock in different markets, and visualize the result of analysis. Provide users a platform for evaluating stocks simply. This system use Amiboker, Python, MySQL, Jupyter Notebook and Plotly to implement the platform and research on the shares of companies listed in New York Stock Exchange from January 1, 1998 to December 31, 2016. Conduct an object-oriented portfolio with technical analysis, fundamental analysis and investment method. Also build a automatic process of back test and analysis by connecting python with program trading software Amibroker. Help users customize the portfolio parameters they focused, and display the results of profit and risk using statistical graphics. The result of the study shows that there are several price momentum factors are highly relevant in rank and profit. When choosing the best group of appropriate fundamental factors as the basic of portfolio can make about 40% compound average growth rate, which means that considering these fundamental factors and other portfolio parameters when selecting stock will have higher benefits.
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