指數追蹤:選股與資金配置之探討

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：20

、訪客IP：3.144.29.213

姓名

吳宗穎(Tsung-Ying Wu) 查詢紙本館藏

畢業系所

財務金融學系

論文名稱

指數追蹤:選股與資金配置之探討
(Improving Index-Tracking Using Gnetic Algorithm)

相關論文

★ 避險基金之績效評估	★ 展望理論與共同基金績效
★ 生命週期基金 :行為財務學觀點	★ 行為特性與投資績效相關性之研究
★ 專業投資人行為特性探討	★ 中小型企業融資缺口與資訊不對稱之探討
★ 九型人格特質與理財偏誤行為之相關性研究	★ 銀行通路轉型策略個案研究
★ 銀行財富管理行銷策略分析-以兩家在台外商銀行為例	★ 羅盤玫瑰可預測型態之探討
★ 巢式與非巢式資產定價理論之比較與檢定	★ 投資者情緒與市場報酬
★ 資產定價模型樣本外績效之檢定	★ 規模效果和元月效應之微觀
★ 因子或特徵:全球觀點	★ 特徵與因子：日本證據

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]

本電子論文使用權限為同意立即開放。
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。
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)

摘要
過去探討指數追蹤之文獻中，大部分皆設定追蹤投資組合為固定權重之投資組合，實際上指數本身之成分股權重並非固定，本研究中主張，欲以固定權重之追蹤投組複製本身為買入持有投資組合之目標指數，將造成追蹤誤差。本文對於過去於指數追蹤問題上之研究加以整理，並提出以一買入持有投資組合追蹤目標指數之模型，本研究以S&P 500指數資料作為實證資料，與過去研究者所提出之模型做一比較。
本文利用S&P 500 指數以及其各成分股於1997年至2002年之日資料進行實證分析。在指數追蹤中的選股問題方面，分別利用二次規劃法模型、市值加權模型以及遺傳演算法選股模型；資金配置問題上，以傳統法建構固定權重投資組合與以遺傳演算法買入持有投資組合之觀念分別決定買進單位數，共建構六種追蹤投資組合投資於樣本外測試期。
綜合而言，以遺傳演算法選股雖然隱含較大之交易成本，但能避免報酬率表現持續向上或向下偏離目標指數報酬率之情況，且投組之價值走勢長期貼近目標指數，較符合指數型基金經理人之目標。另外，以建構買進持有投資組合之觀念取代以建構固定權重投組之方法決定各投組成份股所需買入之單位數，將能有效降低追蹤誤差。

摘要(英)

Abstract
Index-tracking problem used to be defined as to construct a constant-weight rebalanced portfolio to chase target index. Since index itself is a buy-and-hold portfolio, we argue that instead of building a constant-weighted tracking portfolio, to construct a buy-and-hold one is more realistic.
Index-tracking problem contains the stock selection problem and the problem of how many shares to buy. In stock selection problem, we discussed optimization model, capitalization-based model and GA selection model. On the other hand, when we try to build a buy-and-hold portfolio, we employed genetic algorithm to solve the complex non-linear problem, and compare the out-of-sample result with the traditional constant-weight rebalance tracking portfolio.
To test our model, we used S&P 500 daily price data from 1997 to 2002, and concluded that GA stock selection model implies higher transaction cost while it could prevent long-term downside or upside biases; the buy-and-hold tracking portfolio leads to a relatively small tracking when we compare it with a constant-weight rebalanced one.

關鍵字(中)

★ 資金配置
★ 選股
★ 遺傳演算法
★ 指數追蹤
★ 買入持有投資組合

關鍵字(英)

★ genetic algorithm
★ index tracking
★ stock selection
★ buy-and-hold portfolio

論文目次

目錄
頁次
目錄……………………………………………………………………i
表目錄………………………………………………………………… iii
圖目錄………………………………………………………………… iv
第一章緒論………………………………………………………… 1
1.1研究背景………………………………………………………………1
1.2研究動機與目的………………………………………………………2
1.3研究架構………………………………………………………………2
第二章文獻回顧………………………………………………3
2.1 目標函數設定………………………………………………………………4
2.2 選股篩選設定………………………………………………………………7
2.3 建立投資組合上的其他問題………………………………………………8
2.4 交易成本與現金管理………………………………………………………9
第三章研究方法……………………………………………………11
3.1 定義指數追蹤問題…………………………………………………………11
3.2 選股………………………………………………………………………17
3.3 資金配置…………………………………………………………………19
3.4 交易成本…………………………………………………………………21
第四章實證結果與分析…………………………...…….…………23
4.1 實證資料…………………………………………………………………23
4.2 績效評估指標……………………………………………………………23
4.3 遺傳演算法之收斂條件…………………………………………………...23
4.4 選股模型與資金配置法之差異比較……………………………………...24
4.5追蹤誤差……………………………………………………………………25
第五章結論………………………………………………….………..28
參考文獻…………………………………………………….…………30
附錄 S&P 500指數成分股變動列表…………………….……...……45
表目錄
頁次
表一選股模型與資金配置法之績效評估 (每月調整)………………………….32
表二選股模型與資金配置法之績效評估 (每季調整) ……………….……..….34
表三選股模型與資金配置法之績效評估 (每半年調整) ………………...…….36
表四選股模型與目標指數之平均報酬差異表…………………………….…….38
圖目錄
頁次
圖一遺傳演算法收斂示意圖…………………………………………………….39
圖二市值加權選股方法下以傳統法及遺傳演算法配置資金之
追蹤誤差比較圖…………………………………………………………….40
圖三二次規劃選股法下以傳統法及遺傳演算法配置資金之
追蹤誤差比較圖…………………………………………………………….41
圖四遺傳演算法選股下以傳統法及遺傳演算法配置資金之
追蹤誤差比較圖…………………………………………………………….42
圖五以市值加權法選股、遺傳演算法配置資金之追蹤投資組合與目標指數
價值走勢比較圖…………………………………………………………….43
圖六以二次規劃法選股、遺傳演算法配置資金之追蹤投資組合與目標指數
價值走勢比較圖…………………………………………………………….44
圖七以遺傳演算法選股、遺傳演算法配置資金之追蹤投資組合與目標指數
價值走勢比較圖……………………………………………………..…..….45

參考文獻

References
[1] Allen, F., R. Karjalainen, (1999)Using genetic algorithms to find technical trading rules. Journal of Financial Economics, 51, 245-271
[2] Ammann, M. and H. Zimmermann (2001), Tracking error and tactical asset allocation. Financial Analysts Journal, 57, 32-43.
[3] Beasley, J. E., N Meade. and T.-J. Chang (1999). Index-tracking. Mimeo,
http://mscmga.ms.ic.ac.uk/jeb/track.html.
[4] Alexander, Carol, (1999), Optimal hedging using cointegration. Philosophical Transactions of the Royal Society of London, Series A-Mathematical Physical and Engineering Sciences, 357, 2039-2058.
[5] Connor, G. and H. Leland (1995), Cash management for index tracking. Financial Analysts Journal, 51, 75-80.
[6] Ferson, Wayne E., and Campbell R. Harvey (1991). "The Variation of Economic Risk Premiums," Journal of Political Economy, 99, 385-415
[7] Francesco, Corielli and Marcellino Massimiliano (2002), Factor Based Index Trading, working paper n.209, Innocenzo Gasparini Institute for Economic Research.
[8] Gilli, M., and E. Kellezi (2001). A global optimization heuristic for portfolio
choice with VaR and expected shortfall. In: Computational Methods in
Decision-making, Economics and Finance (P. Pardalos and D.W. Hearn,
Ed.). Applied Optimization Series.
[9] Gilli, M. and E. Këllezi (2001), Threshold accepting for index tracking. Working paper available from the first author at Department of Econometrics, University of Geneva, 1211 Geneva 4, Switzerland,
[10] Holland, J. (1975), Adaptation in natural and artificial systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. University of Michigan Press.
[11] Jonsson, H., P. Madjidi and M.G. Nordahl (1997). Evolution of trading rules for the FX market or how to make money out of gp.
[12] Konno, H. and A. Wijayanayake (2001). Minimal cost index-tracking under nonlinear transaction costs and minimal transaction unit constraints. Journal
of Theoretical and Applied Finance.
[13] Larsen, G.A. and B.G Resnick. (1998), Empirical insights on indexing. The Journal of Portfolio Management, 25, 51-60.
[14] Markowitz, H. (1952), Portfolio selection. Journal of Finance, 7, 77-91.
[15] Markowitz, H. (1959), Portfolio selection: efficient diversification of investments. Wiley.
[16] Meade, N. and G.R. Salkin (1990), Developing and maintaining an equity index fund. Journal of the Operational Research Society, 41, 599-607.
[17] Rohweder, H.C., (1998), Implementing stock selection ideas: does tracking error optimization do anything good? The Journal of Portfolio Management, 24, 49-59.
[18] Pope, P.F. and P.K. Yadav (1994), Discovering errors in tracking error. The Journal of Portfolio Management, 20, 27-32.
[19] Roll, R. (1992), A mean/variance analysis of tracking error. The Journal of Portfolio Management, 18, 13-22.
[20] Rudd A. (1980), Optimal selection of passive portfolios. Financial Management 57-66.
[21] Rudolf, M., H.-J. Wolter and H. Zimmermann (1999), A linear model for tracking error minimization. Journal of Banking & Finance, 23, 85-103.
[22] Speranza, M.G. (1993), Linear Programming Models for Portfolio. Optimizationtion. Finance, 14, 107-123.
[23] Standard & Poor, http://www.spglobal.com/ (2002).

指導教授

周賓凰(Pin-Huang Chou)

審核日期

2003-6-26

推文