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題名 均值迴歸或動能? 配對交易策略分析
Mean Reversion or Momentum? A Pairs Trading Analysis
作者 王雅醇
Wang, Ya-Chun
貢獻者 羅秉政<br>林士貴
Kendro Vincent<br>Lin,Shih-Kuei
王雅醇
Wang, Ya-Chun
關鍵詞 配對交易
均值迴歸
價格偏離
Pairs trading
Mean reversion
Price deviation
日期 2025
上傳時間 4-Aug-2025 14:32:09 (UTC+8)
摘要 根據歷史資料統計，若自 1990 年起持有那斯達克 500 指數成分股，平均年化報酬率約為 29.5%，顯示長期持有雖具潛在報酬，但其間波動劇烈、回撤風險亦高。因此，尋求能在短期內穩定獲利的策略，如配對交易，便成為具吸引力的選擇。 配對交易為一種統計套利策略，透過找出歷史走勢相似的股票對，在其價差偏離時進行「買低賣高」操作，以期價差回歸後獲利。過去研究指出，配對交易在市場效率較低時效果顯著，但近年因資訊傳播與金融科技進步，策略報酬逐漸下降。 本研究將市場價格建構為「預期價格 + 誤差項」的架構，嘗試統整均值迴歸與動能邏輯，探討價格偏離後的行為模式。我們以 1990 至 2023 年 NASDAQ-500 成分股為樣本，建構動態配對交易策略，並引入懲罰參數以調整配對組合結構與交易頻率。結果顯示，適當的懲罰參數能簡化投資組合，提升報酬，且價格偏離在部分情況下具趨勢延續特性。 本研究有助於投資者在制定量化策略時，兼顧均值迴歸與動能行為，提升策略穩定性與適應性。
According to historical data, a buy-and-hold strategy on NASDAQ-500 stocks yields an average annualized return of approximately 29.5%, though with high volatility. This has increased interest in short-term strategies like pairs trading, which exploit temporary price divergences between historically co-moving stocks. This study models asset prices as the sum of expected value and noise, bridging mean-reversion and momentum theories. Using NASDAQ-500 data from 1990 to 2023, we implement a dynamic pairs trading strategy with a penalty parameter to adjust portfolio complexity and trading frequency. Empirical results show that proper penalty settings can simplify portfolio construction and improve returns. Additionally, not all price divergences revert—some follow trends—highlighting the importance of understanding underlying market dynamics. These insights support more adaptive and robust quantitative trading strategies.
參考文獻 Abadie, A., & L’Hour, J. (2021). A Penalized Synthetic Control Estimator for Disaggregated Data. Journal of the American Statistical Association, 116(536), 1817–1834. Avellaneda, M., & Lee, J. H. (2010). Statistical arbitrage in the US equities market. Quantitative Finance, 10(7), 761–782. Caldeira, J. F., & Moura, G. V. (2013). Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy. Revista Brasileira de Finanças, 11(1), 49–80. Chen, H., Chen, S., Chen, Z., & Li, F. (2019). Empirical Investigation of an Equity Pairs Trading Strategy. Management Science, 65(1), 370–389. Do, B., & Faff, R. (2010). Does Simple Pairs Trading Still Work? Financial Analysts Journal, 66(4), 83–95. Elliott, R. J., Van Der Hoek, J., & Malcolm, W. P. (2005). Pairs trading. Quantitative Finance, 5(3), 271–276. Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 797–827. Jacobs, H., & Weber, M. (2015). On the Determinants of Pairs Trading Profitability. Journal of Financial Markets, 23, 75–97. Nath, P. (2003). High Frequency Pairs Trading with U.S. Treasury Securities: Risks and Rewards for Hedge Funds. Working Paper. Rad, H., Low, R. K. Y., & Faff, R. (2016). The profitability of pairs trading strategies: Distance, cointegration and copula methods. Quantitative Finance, 16(10), 1541–1558.
描述 碩士
國立政治大學
金融學系
112352010
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112352010
資料類型 thesis
dc.contributor.advisor 羅秉政<br>林士貴zh_TW
dc.contributor.advisor Kendro Vincent<br>Lin,Shih-Kueien_US
dc.contributor.author (Authors) 王雅醇zh_TW
dc.contributor.author (Authors) Wang, Ya-Chunen_US
dc.creator (作者) 王雅醇zh_TW
dc.creator (作者) Wang, Ya-Chunen_US
dc.date (日期) 2025en_US
dc.date.accessioned 4-Aug-2025 14:32:09 (UTC+8)-
dc.date.available 4-Aug-2025 14:32:09 (UTC+8)-
dc.date.issued (上傳時間) 4-Aug-2025 14:32:09 (UTC+8)-
dc.identifier (Other Identifiers) G0112352010en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158588-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 金融學系zh_TW
dc.description (描述) 112352010zh_TW
dc.description.abstract (摘要) 根據歷史資料統計，若自 1990 年起持有那斯達克 500 指數成分股，平均年化報酬率約為 29.5%，顯示長期持有雖具潛在報酬，但其間波動劇烈、回撤風險亦高。因此，尋求能在短期內穩定獲利的策略，如配對交易，便成為具吸引力的選擇。 配對交易為一種統計套利策略，透過找出歷史走勢相似的股票對，在其價差偏離時進行「買低賣高」操作，以期價差回歸後獲利。過去研究指出，配對交易在市場效率較低時效果顯著，但近年因資訊傳播與金融科技進步，策略報酬逐漸下降。 本研究將市場價格建構為「預期價格 + 誤差項」的架構，嘗試統整均值迴歸與動能邏輯，探討價格偏離後的行為模式。我們以 1990 至 2023 年 NASDAQ-500 成分股為樣本，建構動態配對交易策略，並引入懲罰參數以調整配對組合結構與交易頻率。結果顯示，適當的懲罰參數能簡化投資組合，提升報酬，且價格偏離在部分情況下具趨勢延續特性。 本研究有助於投資者在制定量化策略時，兼顧均值迴歸與動能行為，提升策略穩定性與適應性。zh_TW
dc.description.abstract (摘要) According to historical data, a buy-and-hold strategy on NASDAQ-500 stocks yields an average annualized return of approximately 29.5%, though with high volatility. This has increased interest in short-term strategies like pairs trading, which exploit temporary price divergences between historically co-moving stocks. This study models asset prices as the sum of expected value and noise, bridging mean-reversion and momentum theories. Using NASDAQ-500 data from 1990 to 2023, we implement a dynamic pairs trading strategy with a penalty parameter to adjust portfolio complexity and trading frequency. Empirical results show that proper penalty settings can simplify portfolio construction and improve returns. Additionally, not all price divergences revert—some follow trends—highlighting the importance of understanding underlying market dynamics. These insights support more adaptive and robust quantitative trading strategies.en_US
dc.description.tableofcontents 第 一章 緒論 1 第 一節 研究目的 1 第 二節 文獻回顧 2 第 二章 研究方法 5 第 一節 估計方法 5 第 二節 擬合過程 6 第 三節 報酬計算 6 第 四節 動能策略 8 第 三章 資料處理結果 10 第 一節 資料處理 10 第 二節 擬合權重 11 第 三節 配對交易單一公司報酬分析 12 第 四章 實證結果 13 第 一節 其他參數對交易之影響 13 第 二節 配對交易報酬 16 第 三節 交易訊號反向操作 16 第 四節 統計分析 19 第 五節 子期間分析 22 第 五章 結論 36 參考文獻 38zh_TW
dc.format.extent 1004093 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112352010en_US
dc.subject (關鍵詞) 配對交易zh_TW
dc.subject (關鍵詞) 均值迴歸zh_TW
dc.subject (關鍵詞) 價格偏離zh_TW
dc.subject (關鍵詞) Pairs tradingen_US
dc.subject (關鍵詞) Mean reversionen_US
dc.subject (關鍵詞) Price deviationen_US
dc.title (題名) 均值迴歸或動能? 配對交易策略分析zh_TW
dc.title (題名) Mean Reversion or Momentum? A Pairs Trading Analysisen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Abadie, A., & L’Hour, J. (2021). A Penalized Synthetic Control Estimator for Disaggregated Data. Journal of the American Statistical Association, 116(536), 1817–1834. Avellaneda, M., & Lee, J. H. (2010). Statistical arbitrage in the US equities market. Quantitative Finance, 10(7), 761–782. Caldeira, J. F., & Moura, G. V. (2013). Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy. Revista Brasileira de Finanças, 11(1), 49–80. Chen, H., Chen, S., Chen, Z., & Li, F. (2019). Empirical Investigation of an Equity Pairs Trading Strategy. Management Science, 65(1), 370–389. Do, B., & Faff, R. (2010). Does Simple Pairs Trading Still Work? Financial Analysts Journal, 66(4), 83–95. Elliott, R. J., Van Der Hoek, J., & Malcolm, W. P. (2005). Pairs trading. Quantitative Finance, 5(3), 271–276. Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 797–827. Jacobs, H., & Weber, M. (2015). On the Determinants of Pairs Trading Profitability. Journal of Financial Markets, 23, 75–97. Nath, P. (2003). High Frequency Pairs Trading with U.S. Treasury Securities: Risks and Rewards for Hedge Funds. Working Paper. Rad, H., Low, R. K. Y., & Faff, R. (2016). The profitability of pairs trading strategies: Distance, cointegration and copula methods. Quantitative Finance, 16(10), 1541–1558.zh_TW