臺灣博碩士論文加值系統

在此篇研究中，我們將利用系統性的方法於台灣加權指數中辨認出道氏理論中的頭肩頂形態，並加以衡量技術指標的效率。首先我們先從資料中篩選出規律出現的天數，並以回歸分析找尋規律與其出現後的累積報酬之關係。其後再建立交易策略，且利用 Fama and French (1993)的三因子模型計算預期報酬，進而估算出異常報酬，經由檢測後，超額報酬皆於統計結果上顯示為顯著。最後，我們進行了模擬交易，希望藉由回測的方式來檢視這樣的交易策略之可行性，結果顯示我們所提出的策略之表現無論是在記入交易成本前後，皆優於簡單買進持有策略與無風險利率，除此之外，回測之結果也顯示我們的交易策略於熊市之獲利明顯高於其他交易時段。上述的結果皆說明道氏理論中的頭肩頂形態內具有某些資訊可供利用以獲取報酬。

In this paper, we propose a systematic approach to recognizing technical patterns, and we apply this method to TAIEX index from 1990 to 2017 to evaluate the effectiveness of technical analysis. Using OLS regression, we find the two technical indicators, head-and-shoulders top (HST) and head-and-shoulders bottom (HSB), are able to predict the accumulative returns after the patterns occur. Using the Fama-and-French (1993) three-factor model as a style benchmark for the accumulative returns, we find that the abnormal returns are statistically significant. At last, we back-test the trading strategies and find that the HST and HSB strategies outperform the sell-and-hold and buy-and-hold benchmarks respectively. The strategy combining both HST and HSB earns about 8% annual returns and around 6% annual returns for time period of five trading days before and after transaction costs respectively. Moreover, we find that the strategies we proposed tend to generate more returns in bear markets than in bull markets.

摘要 i
ABSTRACT ii
誌謝 iii
Content iv
List of Tables v
List of Figures vi
Chapter 1. Introduction 1
1.1 Research Background 1
1.2 Research Motivation and Purpose 2
1.3 Thesis Structure 2
Chapter 2. Literature Review 3
2.1 Technical Analysis 3
2.2 Head-and-Shoulders Patterns 4
2.3 Efficient Market Hypothesis 5
2.4 Performance Measurement 5
2.4.1 Sharpe Ratio 6
2.4.2 Sortino Ratio 6
Chapter 3. Data and Methodology 7
3.1 Research Samples and Periods Selection 7
3.2 Definitions of Technical Patterns 7
3.3 OLS Regression 14
3.4 Trading Strategy 15
3.5 Performance Measurement 16
Chapter 4. Empirical Results 18
4.1 Recognition of the Patterns 18
4.2 Abnormal Returns 19
4.3 OLS Regression 20
4.4 Wilcoxon Signed-ranked Test Results 21
4.5 Simulation Trading Results 21
4.6 Head-and-shoulders Strategy 25
Chapter 5. Conclusions and Suggestions 27
5.1 Conclusions 27
5.2 Suggestions for Further Research 27
References 29
Appendices 32

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