Asset Allocation Based on the Black-Litterman and GARCH Models

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：35

、訪客IP：18.119.125.7

姓名

林煒紘(Wei-hung Lin) 查詢紙本館藏

畢業系所

統計研究所

論文名稱

(Asset Allocation Based on the Black-Litterman and GARCH Models)

相關論文

★ Structure learning for hierarchical Archimedean copulas	★ Sensitivity analysis of credit derivatives
★ 在 Black-Sholes 模型下運用選擇權資料進行動態避險之比較	★ A Dynamic Rebalancing Strategy for Portfolio Allocation
★ A Multivariate Markov Switching Model for Portfolio Optimization	★ 基於 Copula 模型的資產配置及台灣股票市場的應用
★ Copula連結時間序列應用在失業率下之建模	★ Calibrating the state price densities using TAIEX options
★ Estimating intensity processes from Credit Default Swaps	★ Copula連結之天氣資料預測
★ Efficient Importance Sampling for Copula Models with Applications	★ 貝氏補值方法應用在行星資料的週期和質量上
★ 信用違約交換之定價	★ 利用重點抽樣的有效率選擇權訂價
★ Improved Mortality Forecasting Using Augmented Data	★ A direct method for calculating Greeks under some L

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

雖然Markowitz 模型在實務上是可用的，但是它仍存在許多缺點，尤其是在估計最適權重時，常會因為參數過度敏感的問題而導致嚴重的估計誤差產生。為了解決這個估計誤差的問題，我們使用Black-Litterman model，藉由它將市場隱含報酬率與投資人的觀點做聯結去修正預期報酬率，此外為了能更準確刻畫投資人之觀點誤差我們也將標準的Black-Litterman model 模型結合不同之GARCH 模型去估計隨時間變化的共變異數矩陣。最後，我們利用台灣股票市場中的五檔產業指數提供了一些實證分析。

摘要(英)

Asset allocation using Markowitz model has many disadvantages, particularly because the optimal weight is sensitive to the estimation error of the model. To overcome the problem of estimation error, we follow Black-Litterman model, where the initial expected returns are linked to market implied return and subjective views of investor for each asset to adjust the expect return. To adjust the heteroscedasticity of the volatility, we further combine the standard Black-Litterman model with several GARCH-typed models to estimate time-varying covariance matrix. Finally, we conduct an empirical analysis using five industry indexes in Taiwan stock market.

關鍵字(中)

★ 馬科維茨
★ Black-Litterman
★ GARCH
★ EGARCH

關鍵字(英)

★ Markowitz
★ Black-Litterman
★ GARCH
★ EGARCH

論文目次

摘要....................................................i
Abstract...............................................ii
誌謝..................................................iii
List of Figures........................................vi
List of Tables.......................................viii
1 Introduction..........................................1
2 Properties of asset returns and time varying volatility model...................................................4
2.1 GARCH model.........................................4
2.2 EGARCH model........................................5
2.3 Time varying covariance of assets...................6
3 Methodology...........................................8
3.1 Markowitz mean-variance model.......................8
3.2 Black-Litterman model..............................11
3.2.1 The market model with implied equilibrium returns................................................12
3.2.2 Investor views and confidence of views...........15
3.2.3 The new combined return model....................17
3.3 Our approaches.....................................19
3.3.1 Absolute view....................................19
3.3.2 Relative view....................................20
4 Empirical Analysis...................................21
4.1 Data and Statistics................................21
4.2 Sample construction................................26
4.3 Empirical comparison...............................28
4.3.1 Estimated weights using Markowitz and the Black-Litterman model........................................28
4.3.2 Performances comparison using various models (lambda = 1)...........................................32
4.3.3 Performances comparison using various models (lambda = 5)...........................................39
4.3.4 Performances comparison using various models (lambda = 10)..........................................46
5 Conclusion...........................................54
Reference..............................................58
Appendix...............................................61

參考文獻

Andrew, B. and K. Winkelmann (1998). Using the Black-Litterman Global Asset Allocation Model: Three Years of Practical Experience. Goldman Sachs Fixed Income Research paper.
Beach, S. L. and A. G. Orlov (2007). An application of the Black–Litterman model with EGARCH-M-derived views for international portfolio management. Financial Market Portfolio management 21, 147–166.
Bertsimas, D., V. Gupta, and I. C. Paschalidis (2012). Inverse Optimization: A New Perspective on the Black-Litterman Model. Journal of Operations Research 60(6), 11–12.
Black, F. and R. Litterman (1991). Asset Allocation: Combing Investors View with Market Eqilibrium. Journal of Fixed Income 1(2), 7–18.
Black, F. and R. Litterman (1992). Global Porfolio Optimization. Financial Analysts Journal 48(5), 28–43.
Brianton, G. (1998). Portfolio Optimization (1 ed.). Macmillan Business, London: Risk Management and Financial Derivatives : A Guide to the Mathematics.
Chopra, V. K., C. R. Hensel, and A. L. Turner (1993). Massaging Mean-Variance Inputs: Returns from Alternative Global Investment Strategies in the 1980s. Journal of Finance 39(7), 845–855.
Christodoulakis, G. A. (2002). Bayesian Optimal Portfolio Selection: the Black-Litterman Approach. Goldman Sachs Fixed Income Research paper.
He, G. and R. Litterman (1999). The Intuition Behind Black-Litterman Model Portfolios. Goldman Sachs Fixed Income Research paper.
Huang, S. T. (2007). Exploring the Optimal Control of Taiwan’s Banking Industry from the Taiwan’s Banking Industry Mergers. Taiwan Electronic Periodical Services
(TEPS) (27), 177–195.
Idzorek, T. (2004). A STEP-BY-STEP GUIDE TO THE BLACK-LITTERMAN MODEL. Working paper.
Mandelbrot, B. (1963). The Variation of Certain Speculative Prices. Journal of Business 36(4), 394–419.
Markowitz, H. (1952). Portfolio Selection. Journal of Finance 7(1), 77–91.
Meucci, A. (2006). Beyond Black-Litterman in Practice: A Five-Step Recipe to Input Views on Non-Normal Markets. Risk Magazine 19(2), 87–92.
Meucci, A. (2010). The Black-Litterman Approach: Original Model and Extensions. The Encyclopedia of Quantitative Finance.
Michaud, R. O. (1989). The Markowitz Optimization Enigma: Is ’Optimized’ Optimal? Financial Analysts Journal 45(1), 31–42.
Morgan, I. G. (1976). Stock prices and Heteroscedasticity. Journal of Business 49(4), 496–508.
Nelson, B. (1991). Conditional Heteroskedasticity in Asset Return: A New Approach. Econometrica 59(2), 347–370.
Ross, S. A. (1976). The Arbitrage Pricing Theory of Capital Assets. Journal Of Economic Theory, 343–362.
Satchell, S. and A. Scowcroft (2000). A demystification of the Black–Litterman model: Managing quantitative and traditional portfolio construction. Journal of Asset Management 1, 138–150.
Tsay, R. S. (2010). Analysis of Financial Time Series (3 ed.). Wiley.
Tsay, R. S. (2013). An Introduction to Analysis of Financial Data with R (3 ed.). Wiley.
Walters, J. (2014). The Black-Litterman Model In Detail. Working paper available on SSRN. http : //papers:ssrn:com/sol3/papers:cfm?abstractid = 1314585.

指導教授

鄧惠文(Huei-wen Teng)

審核日期

2015-7-29

推文