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研究生： 林韋成
Lin, Wei-Cheng
論文名稱： 利用逐步預測力優劣檢定和拔靴真實性檢定探討技術分析在期貨市場之有效性
Examining the Performance of Technical Analysis in Futures Markets with the SSPA Test and the BRC
指導教授： 顏盟峯
YEN, MENG-FENG
學位類別： 碩士
Master
系所名稱： 管理學院 - 財務金融研究所
Graduate Institute of Finance
論文出版年： 2010
畢業學年度： 98
語文別： 英文
論文頁數： 39
中文關鍵詞： 技術分析 、交易規則 、資料探勘誤差 、拔靴真實性檢定 、逐步預測力優劣檢定 、定態拔靴
外文關鍵詞： technical analysis, trading rule, data snooping bias, BRC, SSPA test, stationary bootstrap
相關次數： 點閱：124  下載：4 
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    • 為了檢驗技術分析的有效性，本篇研究將更多的交易規則（20,970條）應用到20個期貨市場並使用逐步預測力優劣檢定及拔靴真實性檢定來探討，並將交易成本及保證金都考慮在內以跟現實狀況更為貼近。我們檢定在整段期間、第一子期間和第二子期間內，最好的交易規則是否能顯著擊敗無風險利率，拔靴真實性檢定的結果顯示：在幾乎所有的期貨市場中，最好交易規則的表現皆能優於無風險利率，但在資料探勘誤差被調整後，這些好的績效能力就會消失，這結果和過去Marshall, Cahan, and Cahan (2008)的文獻結果一致。僅在第二子期間，影響定態拔靴之區間大小的幾何分配之兩參數值下，逐步預測力優劣檢定能在S&P500期貨市場中各找出兩條績效顯著為正的交易規則，此外，逐步預測力優劣檢定亦揭露了資料探勘誤差的問題；在三個期間的許多期貨市場中，由於逐步預測力優劣檢定的p-value都較拔靴真實性檢定的p-value還小，因而提供了更好的檢定力。在拔靴真實性檢定及逐步預測力優劣檢定的定態拔靴過程中，影響定態拔靴之區間大小的幾何分配之不同參數值會產生不同的p-value，造成一些分析上的影響，和之前的文獻相比，本篇研究同時採用四個參數值，因而能有更完整的考量。

    To examine the superior performance of technical analysis, we apply a larger universe of 20,970 technical trading rules to twenty futures markets using the Bootstrap Reality Check (BRC) and the stepwise superior predictive ability (SSPA) test. The transaction cost and the margin are taken into account for a practical manner. We test whether the best trading rule can significantly beat the benchmark of the risk-free rate in the full period, as well as in the first sub-period and the second sub-period. The results of the BRC show that the best trading rules are superior to the benchmark for almost all the futures markets; however, the outperformance vanishes after adjusting the data snooping bias, providing a consistency with the previous study of Marshall, Cahan, and Cahan (2008). The SSPA test merely identifies two outperforming trading rules for the S&P500 futures market under two values of the smooth parameter for the geometric distribution for the stationary bootstrap block size in the second sub-period. Besides, the SSPA test also discloses the data snooping bias between the nominal p-value and the SSPA test p-value and provides more testing power than the BRC due to the smaller SSPA test p-value for most futures markets in all the three periods. The fours values of smooth parameter we conduct for the geometric distribution for the stationary bootstrap block size of the BRC and the SSPA test make p-value differ from each other, causing some influence for analysis.
    Adopting more values of this smooth parameter comparing to the previous works hence enable this paper more complete.

    CONTENTS Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Motivation and Objectives 2 1.3 Major Findings 3 1.4 Contribution 4 Chapter 2 Literature Review 5 2.1 Profitability of Technical Analysis Suffers from the Data Snooping Bias 5 2.2 The Proposition of the BRC and Its Application to the DJIA 6 2.3 The Proposition of the SPA Test and Further the SRC 7 2.4 The Application of the BRC to the Fifteen Futures Markets 7 2.5 The Proposition of the SSPA Test Based on the SPA Test 8 2.6 The Application of the SPA Test to the Ten Futures Markets 8 Chapter 3 Data and Methodology 10 3.1 Trading Rules 10 3.1.1 Filter Rules (FR) 10 3.1.2 Support and Resistance Rules (SR) 11 3.1.3 Channel Breakout Rules (CB) 11 3.1.4 Moving Average Rules (MA) 12 3.1.5 On-Balance Volume Average Rules (OBV) 13 3.2 Data 13 3.3 Approaches of Evaluation 17 3.3.1 The BRC 17 3.3.2 The SPA Test 18 3.3.3 The SRC 19 3.3.4 The SSPA Test 19 3.4 Computation of Returns 20 Chapter 4 Empirical Results 23 Chapter 5 Conclusions 32 5.1 Suggestions 33 References 38 TABLE OF CONTENTS TABLE 1 THE SUMMARY STATISTICS FOR EACH OF THE TWENTY FUTURES MARKETS 16 TABLE 2 RESULTS OF THE BRC – THE FULL PERIOD 26 TABLE 3 RESULTS OF THE SSPA TEST – THE FULL PERIOD 27 TABLE 4 RESULTS OF THE BRC – THE FIRST SUB-PERIOD 28 TABLE 5 RESULTS OF THE SSPA TEST – THE FIRST SUB-PERIOD 29 TABLE 6 RESULTS OF THE BRC – THE SECOND SUB-PERIOD 30 TABLE 7 RESULTS OF THE SSPA TEST – THE SECOND SUB-PERIOD 31 APPENDIX A. PARAMETERS OF TECHNICAL TRADING RULES 35 APPENDIX B. THE SAMPLE PERIOD AND THE CONTRACT PROFILE OF TWENTY FUTURES MARKETS 36

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