雙因子選股邏輯對投資組合績效影響之研究

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姓名

李權恒(Chuan-Heng Li) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

雙因子選股邏輯對投資組合績效影響之研究
(Performance Evaluation for Stock Selection Strategies of Two Factor Analysis)

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至系統瀏覽論文 (2026-7-1以後開放)

摘要(中)

本研究旨在探討因子選股策略在現代金融市場中的應用與效果，特別
是雙因子選股模型在實際投資中的性能比較。隨著大數據技術和量化分析方法
的發展，因子選股已成為識別投資機會的重要工具。本研究採用交集篩選法、
過濾篩選法、加權內插法與加權排名法四種不同的雙因子選股模型進行實證分
析，通過對比各模型在相同回測條件下的表現，評估它們對投資組合績效的影
響。結果顯示，不同的選股策略對於提升回報率及風險管理具有顯著差異。本
研究開發了一個股票回測工具，支援因子分析，並通過多種回測指標檢視績
效。研究結果為投資者提供了一套更客觀、結構化的選股框架，幫助他們在多
變的市場環境中做出更精確的投資決策。

摘要(英)

This study aims to explore the application and effectiveness of factor-based stock selection strategies in modern financial markets, with a particular focus on the
performance comparison of two-factor stock selection models in practical investments. With the development of big data technology and quantitative analysis methods, factor-based stock selection has become an important tool for identifying
investment opportunities. This study employs four different two -factor stock election models: Intersection screening method, Filter screening method, Weighted interpolation method, and Weighted ranking method, to conduct empirical analysis.
By comparing the performance of each model under the same backtesting conditions,
the study evaluates their impact on portfolio performance. The results indicate
significant differences among the stock selection strategies in terms of improving
returns and managing risk. This research develops a stock backtesting tool that
supports factor analysis and examines performance through various backtesting
indicators. The findings provide investors with a more objective and structured stock
selection framework, assisting them in making more precise investment decisions in a
volatile market environment.

關鍵字(中)

★ 量化交易
★ 因子選股
★ 股市回測平台
★ 金融大數據
★ Python

關鍵字(英)

★ Quantitative Trading
★ Factor-based Stock Selection
★ Stock Market Backtesting Platform
★ Financial Big Data
★ Python

論文目次

摘要 I
ABSTRACT II
目錄 III
圖目錄 VII
表目錄 IX
一、緒論 1
1.1 研究背景 1
1.2 研究動機 1
1.3 研究目的 3
二、文獻回顧 5
2.1 量化交易 5
2.2 因子選股 5
2.3 雙（多）因子的綜效 6
2.4 推論統計 8
2.4.1 Shapiro-Wilk 檢定 8
2.4.2 Mann-Whitney U檢定 8
2.4.3 Kruskal-Wallis 檢定 8
2.4.4 Dunn 事後檢定 8
2.4.5 獨立樣本 t 檢定 9
2.4.6 ANOVA檢定 9
2.5 OLS回歸分析 10
2.6 主導因子 11
三、系統設計與實作 12
3.1 系統架構 12
3.1.1 資料存取層 12
3.1.2 商業邏輯層 13
3.1.3 展示層 16
3.2 雙因子選股模型設計 16
3.2.1 交集篩選法 17
3.2.2 過濾篩選法 18
3.2.3 加權內插法 20
3.2.4 加權排名法 22
3.3 回測績效比較模型 24
3.3.1 獲利能力分析 24
3.3.2 抗風險能力分析 24
3.3.3 分散風險能力分析 25
3.3.4 預測能力分析 25
3.3.5 流動性分析 25
3.4 研究流程 26
3.4.1 常態分佈檢驗 27
3.4.2 驗證研究問題1 27
3.4.3 驗證研究問題2 28
3.4.4 驗證研究問題3 28
3.4.5 驗證研究問題4 28
3.4.6 驗證研究問題5 28
四、系統驗證與分析 30
4.1 實驗變數 30
4.2 回測參數 32
4.3 實驗設計 33
4.3.1 實驗流程 33
4.3.2 環境設定 33
4.4 實驗結果 34
4.4.1 實驗一檢視回測績效是否呈常態分佈 34
4.4.2 實驗二檢視雙因子是否優於單因子選股 38
4.4.3 實驗三四種雙因子選股模型間是否存在差異 41
4.4.4 實驗四兩種加權雙因子選股模型間是否存在差異 44
4.4.5 實驗五驗證過濾篩選法的入選股數量是否顯著大於過濾篩選法47
4.4.6 實驗六檢視是否存在特定因子搭配特定選股模型組合其各指標能夠顯著優於其他組合 48
五、結論 60
5.1 結論 60
5.2 研究限制 61
5.3 未來建議 62
參考文獻 63

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指導教授

許智誠(Jyh-Cheng Hsu)

審核日期

2024-7-4

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