博碩士論文 942205022 詳細資訊




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:25 、訪客IP:18.227.140.54
姓名 彭婕妤(Chieh-yu Peng)  查詢紙本館藏   畢業系所 統計研究所
論文名稱 資產配置的學習效果與其實證研究
(The learning effect of an asset allocation and its empirical study.)
相關論文
★ 特徵與因子:日本證據★ 全球反向策略之研究
★ 隨機利率下之投資組合最佳化★ 統計套利—以相對隱含波幅價差交易對台指選與摩台指選套利
★ 以平均變異數方法對美國風險性資產作投資組合分析★ 評價氣候型衍生性商品之一般化模型
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]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本研究旨在探討只有一個風險資產與一個無風險資產所構成的簡單的投資組合,隨著時間的變化,投資在風險資產上的權重(weight)應該如何選擇,才可以使投資者在投資期間做適當的資產配置,使投資者的期末期望效用最大化。在本文中,我們主要是探討投資人除了在期初做資產配置之外,在到期前的各期也可根據所獲得的先驗資訊,重新更改原有的投資組合。此外,我們運用動態規劃(dynamic programming)與貝式模型的觀念來學習投資在風險資產上的短視近利權重(myopic weight)。實證的部分採用臺灣加權指數、日本Nikkei 225指數與美國S&P 500指數的報酬率,觀察後驗分配的平均數、變異數與投資在風險資產上的短視近利權重隨著時間經過所產生的變化。
摘要(英) The purpose of this paper is to investigate a simple portfolio problem with one risky asset and one risk-free asset: how we choose the weight on the risky asset in order to maximize the expected utility.We consider an investor who rebalances his portfolio continually as more and more information is acquired till the end of the investment horizon. In particular,the investor learns about the parameter values via a Bayesian model and determines the portfolio weight by dynamic programming principle.Empirically,we adopt the return of Taiwan Stock Index,Nikkei 225 Index and S&P 500 index to see the mean and variance of the posterior distribution and the weight on the risky asset as time passes.
關鍵字(中) ★ 短視近利權重
★ 資產配置
★ 動態規劃
關鍵字(英) ★ asset allocation
★ myopic weight
★ dynamic programming
論文目次 1. 研究動機........................................................................................................................................1
2. 文獻回顧........................................................................................................................................2
2.1 平均變異數最佳化(Mean-Variance Optimization,MVO)....................................................3
2.2 戰術性資產配置(tactical asset allocation)...............................................................................4
2.3 動態規劃(Dynamic Programming)..........................................................................................5
2.4 貝式模型在投資組合上的選擇與修正.......................................................................................6
2.5 無資訊先驗分佈(non-subjective prior)...................................................................................8
2.6 常態貝式估計(Normal Bayes estimators)之分佈..................................................................13
3. 投資者的決策問題.......................................................................................................................15
3.1 離散時間.....................................................................................................................................15
3.2 連續時間.....................................................................................................................................18
3.2.1 風險資產上的短視近利權重..................................................................................................18
3.2.2 風險資產上經由學習所得到的權重......................................................................................22
4. 實證研究與模擬...........................................................................................................................27
4.1 資料來源與檢定.........................................................................................................................27
4.1.1 資料來源..................................................................................................................................27
4.1.2 檢定資料的常態性..................................................................................................................31
4.2 日本Nikkei 225指數...................................................................................................................32
4.2.1 採用先驗分佈與非主觀先驗分佈,平均數與變異數的後驗分配的參數的變化.................32
4.2.2 變異數已知與未知時短視近利的風險資產投資比重的差異..............................................33
4.3 模擬日本Nikkei 225指數............................................................................................................35
4.3.1 採用先驗分佈與非主觀先驗分佈,平均數與變異數的後驗分配的參數的變化..................35
4.3.2 變異數已知與未知時短視近利的風險資產投資比重的差異.36
4.4 美國S&P 500指數......................................38
4.4.1 採用先驗分佈與非主觀先驗分佈,平均數與變異數的後驗分配的參數的變化.............................................38
4.4.2 變異數已知與未知時短視近利的風險資產投資比重的差異.39
4.5 模擬美國S&P 500指數..................................41
4.5.1 採用先驗分佈與非主觀先驗分佈,平均數與變異數的後驗分配的參數的變化.............................................41
4.5.2 變異數已知與未知時短視近利的風險資產投資比重的差異.42
4.6 日本與美國結果的比較.................................44
5. 結論..................................................46
參考文獻.................................................47
參考文獻 1. Bernardo, J.M. and Ramon, J.M. (1998). An Introduction to Bayesian Reference Analysis:Inference on the Ratio of Multinomial Parameters. The Statistician 47,101-135.
2. Box, G.E.P and Taio, G.C. (1973). Bayesian Inference in Statistical Analysis. Reading: Addison-Wesley.
3. Brennan, Michael J. (1998). The Role of Learning in Dynamic Portfolio Decisions. European Finance Review 1,295-306.
4. Brennan, Michael J., Schwartz,Eduardo S. and Lagnado, Ronald. (1997). Strategic Asset Allocation. Journal of Economic Dynamics and control 21,1377-1403.
5. Cornuejols, Gerard and Tutuncu, Reha. Optimization Method in Finance.
6. Cvitanic, Jaksa and Zapatero, Fernando. Introduction to The Economics and Mathematics of Financial Markets.
7. Gray, Philip. (2002). Bayesian Estimation of Financial Models. Accounting and Finance 42,111-130.
8. Hakansson, N.H. (1970). Optimal investment and consumption strategies under risk for a class of utility functions. Econometrica 38,587-607.
9. Jeffreys, H. (1961). Theory of Probability(3ed). Oxford: Clarendon Press.
10. Kass, R.E. (1990). Data-translated Likelihood and Jeffereys' rule. Biometrika 77,104-114.
11. Liptser, R.S. and Shiryayev, A.N. (1977). Statistics of random processes. Chapter 10.
12. Merton, R.C. (1971). Optimal consumption and portfolio rules in a continuous-time model. Journal of Economic Theory 3,373-413.
13. Merton, R.C. (1990). Continuous-Time Finance. Blackwell, Oxford.
14. Mossin, J. (1968). Optimal Multi-period Portfolio Policies. Journal of Business,215-229.
15. Samuelson, Paul A. Lifetime Portfolio Selection by Dynamic Stochastic Programming. The Review of Economics and Statistics 51(3),239-246.
16. Vanguard Investment Counseling & Research. A Primer on Tactical Asset Allocation Strategy Evaluation.
17. Winkler, Robert L. (1973). Bayesian Models for Forecasting Future Security Prices. The Journal of Financial and Quantitative Analysis 8(3),387-405.
18. Winkler, Robert L. and Barry, Christopher B. (1975). A Bayesian Model for Portfolio Selection and Revision. Journal of Finance 30(3),179-192.
19. Samuel Kotz、吳喜之和謝邦昌 (2001). 現代貝式統計學及其應用,台灣知識庫.
指導教授 繆維正(Wei-cheng Miao) 審核日期 2007-6-22
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明