博碩士論文 107225022 詳細資訊




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姓名 戴育詳(Yu-Hsiang Tai)  查詢紙本館藏   畢業系所 統計研究所
論文名稱
(Intraday Pairs Trading on Taiwan Semiconductor Companies through Mean Reverting Processes)
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摘要(中) 為了使用高頻資料做配對交易,這篇論文回顧了 Liu 、 Chang 、 Geman 在 2017 年提出的 " 雙
重均值回歸過程 " 模型。基於這個模型,我們使用台灣的股市資料去做回測。我們一共挑
選並記錄了 68 間台灣半導體公司的股票資料。同時為了更貼近實際情況,我們也在這篇論
文裡介紹了一些重要的交易規則和策略。對於 2019/03/18 至 2019/10/24 這段期間的回測結
果為30%的年化報酬率與4.37的年化夏普比率。
摘要(英) In order to execute pairs trading on high frequency data, this thesis reviews ’doubly
mean-reverting processes,’ which was introduced in Liu, Chang, and Geman (2017). Based on
this model, we consider the back-testing driven by the Taiwan stock market data. There are
68 companies in Taiwan semiconductor industry group selected and recorded from Taiwan
Stock Exchange (TWSE). Some specific important trading rules and the corresponding
trading strategies are introduced. In empirical studies, we show the efficiency of the modified
strategy in terms of 30% annualized return and 4.37 annualized Sharpe ratio over the period
from 2019/03/18 to 2019/10/24.
關鍵字(中) ★ 配對交易
★ 高頻資料
★ 雙重均值回歸模型
★ 年化報酬率
★ 年化夏普比率
關鍵字(英) ★ Pairs trading
★ High frequency data
★ Doubly mean-reverting processes
★ Annualized return
★ Annualized Sharpe ratio
論文目次 Contents
摘 要 i
Abstract ii
List of Figures v
List of Tables vi
Chapter1: Introduction 1
Chapter2: Model reviewing: Doubly mean-reverting processes (Liu, Chang,
and Geman (2017)) 4
2.1 Model specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Model calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2.1 Calibration for L(t) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2.2 Calibration for Y (t) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Pairs chosen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Chapter3: Trading strategy on Taiwan stock market 17
3.1 Mid-price . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 Transaction costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3 Inbalance on the both side in one pair . . . . . . . . . . . . . . . . . . . . . . 19
3.4 Open and Close position timing . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.5 Margin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.6 Restriction and Termination . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.6.1 Restriction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.6.2 Termination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.7 Return Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.8 Hyperparameters tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Chapter4: Empirical Study 27
4.1 Data description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.2 Back testing results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.3 Counterexamples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Chapter5: Conclusion 33
References 34
Appendix 37
參考文獻 References
Björk, Tomas. 2009. Arbitrage Theory in Continuous Time. Oxford university press.
Caldeira, João, and Guilherme V Moura. 2013. “Selection of a Portfolio of Pairs Based on
Cointegration: A Statistical Arbitrage Strategy.” Available at SSRN 2196391.
Chang, Hao-Han, Tian-Shyr Dai, Kuan-Lun Wang, Chao-Hsien Chu, and Jun-Zhe Wang.
2020. “Improving Pair Trading Performances with Structural Change Detections and Revised
Trading Strategies.” In 2020 International Conference on Pervasive Artificial Intelligence
(Icpai), 105–9. IEEE.
Chen, Cathy WS, Max Chen, and Shu-Yu Chen. 2014. “Pairs Trading via Three-Regime
Threshold Autoregressive Garch Models.” In Modeling Dependence in Econometrics, 127–40.
Springer.
Chen, Cathy WS, Zona Wang, Songsak Sriboonchitta, and Sangyeol Lee. 2017. “Pair Trading
Based on Quantile Forecasting of Smooth Transition Garch Models.” The North American
Journal of Economics and Finance 39: 38–55.
Clegg, Matthew, and Christopher Krauss. 2018. “Pairs Trading with Partial Cointegration.”
Quantitative Finance 18 (1): 121–38.
Elliott, Robert J, John Van Der Hoek*, and William P Malcolm. 2005. “Pairs Trading.”
Quantitative Finance 5 (3): 271–76.
Gatev, Evan, William N Goetzmann, and K Geert Rouwenhorst. 2006. “Pairs Trading:
Performance of a Relative-Value Arbitrage Rule.” The Review of Financial Studies 19 (3):
34
797–827.
Glasserman, Paul. 2013. Monte Carlo Methods in Financial Engineering. Vol. 53. Springer
Science & Business Media.
Huang, Chien-Feng, Chi-Jen Hsu, Chi-Chung Chen, Bao Rong Chang, and Chen-An Li.
2015. “An Intelligent Model for Pairs Trading Using Genetic Algorithms.” Computational
Intelligence and Neuroscience 2015.
Liu, Bo, Lo-Bin Chang, and Hélyette Geman. 2017. “Intraday Pairs Trading Strategies on
High Frequency Data: The Case of Oil Companies.” Quantitative Finance 17 (1): 87–100.
Miao, George J. 2014. “High Frequency and Dynamic Pairs Trading Based on Statistical
Arbitrage Using a Two-Stage Correlation and Cointegration Approach.” International Journal
of Economics and Finance 6 (3): 96–110.
Rad, Hossein, Rand Kwong Yew Low, and Robert Faff. 2016. “The Profitability of Pairs
Trading Strategies: Distance, Cointegration and Copula Methods.” Quantitative Finance 16
(10): 1541–58.
Ross, Sheldon, ed. 2013. “Simulation.” In, Fifth Edition. Academic Press.
Ross, Sheldon M. 2014. Introduction to Probability Models. Academic press.
Ruppert, David. 2014. Statistics and Finance: An Introduction. Springer.
Schmidt, Arlen David. 2009. “Pairs Trading: A Cointegration Approach.”
Shreve, Steven E. 2004. Stochastic Calculus for Finance Ii: Continuous-Time Models. Vol.
11. Springer Science & Business Media.
35
Vidyamurthy, Ganapathy. 2004. Pairs Trading: Quantitative Methods and Analysis. Vol. 217.
John Wiley & Sons.
Wilmott, Paul, Susan Howson, Sam Howison, Jeff Dewynne, and others. 1995. The Mathe-
matics of Financial Derivatives: A Student Introduction. Cambridge university press.
指導教授 孫立憲(Li-Hsien Sun) 審核日期 2021-1-18
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