![]() |
以作者查詢圖書館館藏 、以作者查詢臺灣博碩士 、以作者查詢全國書目 、勘誤回報 、線上人數:14 、訪客IP:3.145.50.27
姓名 林柏年(Bo-Nian Lin) 查詢紙本館藏 畢業系所 資訊管理學系 論文名稱 以量化交易驗證類股輪動策略之挑選原則與績效評估— 以美股為例
(Evaluating the Selection Criteria for Sector Rotation via Quantitative Trading on Stocks in Major U.S. Exchanges)相關論文 檔案 [Endnote RIS 格式]
[Bibtex 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
[下載]
- 本電子論文使用權限為同意立即開放。
- 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
- 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
摘要(中) 在股票市場會將位於相同產業之公司歸於同一類當中形成類股,由於同一類股內的公司屬於同一產業所進行的商業活動大致相同,因此產業趨勢以及所受到的外部經濟影響也趨於一致,因此同一類股內的股票走勢彼此之間具備高度的關聯性。現今類股輪動被動輪動策略之研究大多著重於價格動能,然而根據過往之文獻顯示成交量動能也對股票之未來走勢習習相關,卻鮮少被納入類股輪動之討論範圍,對此本研究參考了許正諺(2021)之研究,對該研究進行延伸探討。
本研究針對許正諺(2021)之研究所提出的成交量動能因子進行跨類股正規化,並對所有動能因子進行正反項選股交叉驗證,並將上述類股選擇方式套用至美股各不同大盤加權指數所包含的公司當中以驗證各項不同挑選方式對類股輪動被動輪動策略之影響。
呈上所述,為驗證上述之各項挑選原則,本研究將建置一個類股輪動量化交易回測系統並利用此系統進行績效回測以驗證各項挑選原則之績效。實驗結果顯示不同公司範圍所試用之類股輪動被動投資策略有很大的異質性,且當採用類股輪動被動輪動投資策略時會出現大者恆大贏者通吃的現象。摘要(英) In the stock market, companies in the same industry will be grouped into the same class to form Sector. Since companies in the same Sector belong to the same industry and carry out roughly same business activities, the industry trends and external economic impacts also tend to be alike, so the movements of stocks in the same Sector are highly correlated with each other. Most of the current research on the Sector rotation strategies cultivated on the price momentum. However, according to the literature, it shows that the volume momentum is also related to the future trend of the stock, but it is rarely included in the discussion of Sector rotation. This study refers to the research of 許正諺 (2021), and extends this research.
Volume momentum for strategies impacts was studied by 許正諺 (2021), and this research would focus on the cross-sector normalization of the all momentum factors which included volume momentum, and those factors were cross-checked for positive and negative stock selection. The above-mentioned Sector selection methods were applied to U.S. stocks index to verify the influence of different selection methods on the Sector rotation strategies.
To sum up, in order to verify the above selection principles, a quantitative Sector rotation backtesting system will be built and used to test the performance. The experimental results demostrate that there is great heterogeneity in the Sector rotation strategies used in different index, and when using the Sector rotation strategies, there is a phenomenon that the winner will take all on market.關鍵字(中) ★ 類股輪動
★ 動能投資
★ 成交量動能
★ 跨類股正規化
★ 移動窗格
★ 量化交易關鍵字(英) ★ Sector Rotation
★ Momentum Investing
★ Volume Momentum
★ CrossSector Normalization
★ Walk Forward Analysis
★ Quantitative Trading論文目次 摘要 i
Abstract ii
致謝辭 iii
圖目錄 vi
表目錄 vii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 4
第二章 文獻探討 6
2.1 類股輪動 6
2.1.1. 簡介 6
2.1.2. 類股輪動投資策略 7
2.1.3. 交易量動能 8
2.2 行業分類(industry classification) 9
2.2.1. 行業分類比較 11
2.3 量化交易(quantitative trading) 11
2.3.1. 移動窗格 12
2.3.2. 技術分析(Technical Analysis) 14
2.4 績效評估指標 15
2.5 多節點運算 15
第三章 系統設計與實作 17
3.1 系統設計 17
3.1.1. 類股公司分類 17
3.1.2. 動能因子選股 17
3.1.3. 計算中選類股績效 23
3.1.4. 總績效計算 23
3.1.5. 系統流程 23
3.2 系統模組 24
3.3 多節點回測系統架構 26
第四章 系統驗證與分析 28
4.1 實驗架構 28
4.1.1. 實驗變數 28
4.1.2. 資料來源 30
4.2 實驗設計 30
4.3 實驗結果分析 31
4.3.1. 正、反項選股分析 33
4.3.2. 分析不同類股層級對類股輪動策略之影響 42
4.3.3. 分析交易濾網對類股輪動策略之影響 54
4.3.4. 選股範圍對類股輪動策略影響之綜合討論 73
4.3.5. 單一投組績效檢視 74
第五章 結論 79
5.1 結論 79
5.2 研究限制 80
5.3 未來建議 80
參考資料 82
附錄一、不同參數下之CAGR以及MDD熱區圖 85
附錄二、正反項選股統計分析 149
附錄三、不同類股層級分析 166
附錄四、交易濾網有效性分析 198
附錄五、不同參數下之MAR熱區圖 231
附錄六、交易濾網有效性分析(MAR) 263參考文獻 Bernanke, B. S., & Kuttner, K. N. (2005). What Explains the Stock Market’s Reaction to Federal Reserve Policy? The Journal of Finance, 60(3), 1221–1257.
Bhojraj, S., Lee, C. M. C., & Oler, D. K. (2002). What’s My Line? A Comparison of Industry Classification Schemes for Capital Market Research. Journal of Accounting Research, 41(5), 745-774.
Campbell, J. Y., Grossman, S. J., & Wang, J. (1993). Trading Volume and Serial Correlation in Stock Returns. The Quarterly Journal of Economics, 108(4), 905-939.
Chebbi, K., Ammer, M. A., & Hameed, A. (2021). The COVID-19 pandemic and stock liquidity: Evidence from S&P 500. The Quarterly Review of Economics and Finance, 81, 134–142.
Conover, C. M., Jensen, G. R., Johnson, R. R., & Mercer, J. M. (2008). Sector Rotation and Monetary Conditions. The Journal of Investing, 17(1), 34-46.
Deng, M., Leippold, M., Wagner, A. F., & Wang, Q. (2022). Stock Prices and the Russia-Ukraine War: Sanctions, Energy and ESG. SSRN Electronic Journal.
Doeswijk, R. (2011). Global Tactical Sector Allocation: A QuantitativeApproach. The Journal of Portfolio Management, 38(1), 29-47.
Doeswijk, R. Q. (2008). The Optimism Cycle: Sell in May. De Economist, 156(2), 175–200.
Hrazdil, K., Trottier, K., & Zhang, R. (2013). A comparison of industry classification schemes: A large sample study. Economics Letters, 118(1), 77–80.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
Lee, C. M. C., & Swaminathan, B. (2000). Price Momentum and Trading Volume. The Journal of Finance, 55(5), 2017–2069.
Moskowitz, T. J., & Grinblatt, M. (1999). Do Industries Explain Momentum? The Journal of Finance, 54(4), 1249–1290.
Nuti, G., Mirghaemi, M., Treleaven, P., & Yingsaeree, C. (2011). Algorithmic Trading. Computer, 44(11), 61–69.
O’Neal, E. S. (2000). Industry Momentum and Sector Mutual Funds. Financial Analysts Journal, 56(4), 37–49.
Pardo, R. (2011). The evaluation and optimization of trading strategies. John Wiley & Sons.
Rapach, D., Strauss, J., Tu, J., & Zhou, G. (2015). Industry Interdependencies and Cross-Industry Return Predictability. SSRN Electronic Journal.
Stangl, J., Jacobsen, B., & Visaltanachoti, N. (2008). Sector Rotation over Business-Cycles. Department of Commerce, College of Business.
Tortoriello, R. (2009). Quantitative strategies for achieving alpha. McGraw Hill.
Gallant, A. R., Rossi, P. E., & Tauchen, G. (1992). Stock prices and volume. The Review of Financial Studies, 5(2), 199-242.
Stovall S. (1996). Standard & Poor’s Guide to Sector Investing. McGraw-Hill.
Murphy, J. J. (2011). Intermarket analysis: profiting from global market relationships. John Wiley & Sons.
Fama, E. F., & French, K. R. (1997). Industry costs of equity. Journal of financial economics, 43(2), 153-193.
Davey, K. J. (2014). Building winning algorithmic trading systems: A trader′s journey from data mining to Monte Carlo simulation to live trading. John Wiley & Sons.
許正諺 (2021)。客製化類股輪動策略之驗證平台設計與驗證。國立中央大學資訊管理學系碩士論文。
陳正佑 (2012)。台股動量策略與反向策略投資績效之研究。國立中山大學財務管理學系博士論文。
鄭皓元 (2018)。以分散式運算分析多商品主副策略最適性之自動化平台設計與驗證。國立中央大學資訊管理學系碩士論文。指導教授 許智誠(Chih-Cheng Hsu) 審核日期 2022-7-7 推文 plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
網路書籤 Google bookmarks
del.icio.us
hemidemi
myshare