臺灣博碩士論文加值系統

本研究旨在探討Black-Litterman模型應用於實務投資操作之績效表現，有別過去相關研究，我們更深入地分析Black-Litterman模型投資人觀點的環節，主要利用三大法人持股的增長動能將資產池分組，再以簡單線性迴歸來發現兩群組間報酬率的相關性，並且試圖以迴歸分析的p值來調整Black-Litterman模型中較難定義的投資人觀點信心值，期能提供大型資金部位之投資者，如共同基金，在實務操作時作為策略結合、參數調整之參考。研究期間為2004年2月18日至2017年4月30日之日資料，實證結果如下:
一、Black-Litterman模型運用於法人買賣超策略，其三年以上長期績效優於傳統Markowitz模型與等權重配置模型，以及大盤指數和被動式投資ETF。
二、隨著資產池內標的數量的增加，Black-Litterman模型展現了相對等權重配置模型與Markowitz模型更好的模型穩定度，其報酬率下滑，波動度上升的傾向不明顯，顯示Black-Litterman模型更適合用於標的數量較高的資產配置上。
三、Black-Litterman模型相對Markowitz平均數-變異數模型配置出更多角化分散風險的投資組合，同時也能夠積極投入績優標的，該投資特性反映在交易成本上，Black-Litterman模型改善了Markowitz模型的高交易成本，同時利用投資人觀點，來追逐比被動式投資更高的投資績效。
四、本研究針對投資人觀點信心的調整提出一新方法，以迴歸式p值調整，實證結果顯示其淨值績效明顯優於τ值設定為0.025和以樣本數調整τ值之投資組合，但並未能勝過τ值設定為1的投資組合。

The main purpose of this study is to test the effectiveness of utilizing Black-Litterman Model on practice investment. As distinguished from previous research, we go deep into the analysis on the part of investor views. The manner to establish our investor views is to do linear regression to analyze the relationship of return between the groups which are overbought and oversold. Furthermore, we try to adjust confidence of investor views by p-value of the regression. This study is aimed to provide all investors, particularly mutual funds, with a model usage guide. The sample period runs from January 1, 2004 to April 30, 2017. The empirical results are as follows:
1. The 3-year or longer effectiveness of strategy following the net long/short of institutional investors in Black-Litterman Model is better than Markowitz Mean-Variance Model and Equal Weighted Model, and also beat the Taiwan Stock Exchange Weighted Index and Yuanta Taiwan 50 ETF.
2. As number of assets in the asset pool increase, Black-Litterman Model shows better stability than Equal Weighted Model and Markowitz Mean-Variance Model. Different from the two models, its return(volatility) would not obviously decrease(increase) when the size of asset pool expanded. The result suggests that Black-Litterman Model is more suitable for the asset allocation in larger asset pool.
3. Black-Litterman Model is able to create a portfolio which is more diversified than what Markowitz Model created. Meanwhile, it is also able to actively invest in the merit assets. The features reflect on the transaction costs, Black-Litterman Model pursues higher effectiveness with investor views and lower costs.
4. The empirical result shows that performance of portfolio under p-value adjustment is obviously better than which theτset to 0.025 and adjusted by the number of samples, but still can not beat the portfolio which theτset to 1.

摘要 Ⅰ
Abstract Ⅱ
目錄 III
表目錄 IⅤ
圖目錄 V
第一章　緒論 1
第一節 研究動機及目的 1
第二節 研究範圍及架構 3
第三節 研究限制 4
第二章　文獻探討 5
第一節 Markowitz平均數-變異數模型 5
第二節 Black-Litterman模型 7
第三節 三大法人買賣超策略 10
第三章　研究方法 12
第一節 資料來源與範圍 12
第二節 BlacK-Litterman模型之建構 12
第三節 BlacK-Litterman模型之運用 20
第四節 三大法人買賣超策略與觀點之建立 22
第四章　實證結果與分析 24
第一節 資料概述 24
第二節 動態觀點建立 26
第三節 Black-Litterman模型運用於法人買賣超策略之績效評估 29
第四節τ值調整之績效評估 42
第五章　結論與建議 47
第一節 結論 47
第二節 後續研究建議 48
參考文獻 49

一、中文部份
1. 范聖培(2014)，三大法人之買賣超行為對股價短期報酬之研究，國立中央大學財務金融學系在職專班，碩士論文。
2. 陳旭光(2011)，投資組合最適化穩健策略與其實證評比之回顧，證交資料，第五九二期。
3. 陳柏青(2009)，Black-Litterman模型於投資型保單的資產配置-以國泰創世紀保單為例，銘傳大學國際企業學系碩士在職專班，碩士論文。
4. 許筌鈞(2012)，利用動能策略建構Black-Litterman模型之投資組合有效性分析-以台灣50指數為例，亞洲大學財務金融學系碩士班，碩士論文。
5. 許溪南、王健聰、黃文芳(2010)，台灣股市三大法人買賣超型態、強度與報酬之關聯性，中華管理評論國際學報，第十三卷第四期。
6. 梁益民(2003)，Black-Litterman模型在國際資產配置之應用，國立中央大學財務金融研究所，碩士論文。
7. 張森林、劉文讓(2014)，三大法人在股票市場的資訊交易行為探討，論文發表於103年度中華經濟研究院與台灣大學暑期學術交流合作成果報告研討會，台北。
8. 黃憶彣(2007)，Black-Litterman模型運用於資產配置-以臺灣十九類股為例，銘傳大學財務金融學系碩士班，碩士論文。
9. 廖哲宏(2007)，Black-Litterman模型在組合型基金的應用，國立政治大學國際經營與貿易研究所，碩士論文。
10. 劉玉珍、高郁惠、陳嘉惠(2002)，投資人偏好與資產配置，臺灣管理學刊，第一卷第二期，頁213-232。
11. 薛龍進(2006)，台灣股市股價指數報酬率與三大法人買賣超互動關係之實證研究，國立中山大學經濟學研究所在職專班，碩士論文。
二、 英文部份
1. Beach and Orlov(2006), An Application of the BlackLitterman Model with EGARCH-M-Derived views for International Portfolio Management, Finance Markets Portfolio Management, 2007, 3:147-166.
2. Best, M. J. and Grauer, R. R., (1991), On the Sensitivity of Mean-Variance Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results, The Review of Financial Studies, Vol. 4, No. 2, 315-342.
3. Beven, A. and Winkelmann, K., (1988), Using the Black-Litterman Global Asset Allocation Model: Three Years of Practical Experience, Goldman Sachs Fixed Income Research Paper.
4. Black, F. and Litterman, R., (1991), Global Asset Allocation with Equities, Bonds, and Currencies, Fixed Income Research, Vol. 2, No. 15-28, 218.
5. Black, F. and Litterman, R., (1992), Global Portfolio Optimization, Financial Analysts Journal, Vol. 48, No. 5, 28-43.
6. Drobetz, W., (2001), How to Avoid The Pitfalls in Portfolio Optimization? Putting the Black-Litterman Approach at Work, Journal of Financial Markets and Portfolio Management, Vol. 15, No. 1, 59-75.
7. Dungey, M., Milunovich, G., Thorp, S. and Yang, M., (2015), Endogenous Crisis Dating and Contagion Using Smooth Transition Structural GARCH. Journal of Banking & Finance, 58, 71–79.
8. Esteky, D. E. and Abdumuminov, S., (2016), Black-Litterman Model: Practical Asset Allocation Model Beyond Traditional Mean-Variance, Bachelor thesis in Mathematics.
9. Fisher, K. L. and Statman, M., (2000), Investor Sentiment and Stock Returns, Financial Analysts Journal, Vol. 56, No. 2, 16-23.
10. Fusai, G. and Meucci, A., (2003), Assessing Views, Risk Magazine, Vol. 16, No. 3, 18-21.
11. He, G. and Litterman, R., (1999), The Intuition Behind Black-Litterman Model Portfolios, Goldman Sachs Asset Management Working Paper.
12. Idzorek, T., (2005), A Step-By-Step Guide to The Black-Litterman Model, Incorporating User-Specified Confidence Levels, Working Paper.
13. Kahn, R. N. and Lemmon, M., (2016), The Asset Manager’s Dilemma: How Smart Beta is Disrupting the Investment Management Industry, Financial Analysts Journal, Vol. 72, No. 1, 15-21.
14. Lee, W., (2000), Advance Theory and Methodology of Tactical Asset Allocation. New York: John Wiley & Sons.
15. Lin, W. H., Teng, H. W., and Yang, C. C., (2016), A Heterogeneous Black-Litterman Model for Portfolio Allocation, Working Paper.
16. Mankert, C., (2006), The Black-Litterman Model – Mathematical and Behavioral Finance Approaches Towards Its Use in Practice, Licentiate Thesis.
17. Markowitz, H. M., (1952), Portfolio Selection, The Journal of Finance, March, 77-91.
18. Michaud, R. O., (1989), The Markowitz Optimization Enigma: Is Optimized Optimal ?, Financial Analysts Journal, January/February, 31-42.
19. Satchell, S. and Scowcroft, A., (2000), A Demystification of the Black-Litterman Model: Managing Quantitative and Traditional Portfolio Construction, Journal of Asset Management, Vol. 1, No. 2, 138-150.
20. Walters, J., (2014), The Black-Litterman Model in Detail, Working Paper.