跳到主要內容

臺灣博碩士論文加值系統

(34.204.180.223) 您好!臺灣時間:2021/08/05 22:27
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:張志豪
研究生(外文):Chih-hao Chang
論文名稱:粗集合理論在股市篩選之應用與期貨組合投資之策略研究
論文名稱(外文):An application of Rough set on stock selection and Research of Investment strategy on combining Future
指導教授:張 廷 政
指導教授(外文):Ting-Cheng Chang
學位類別:碩士
校院名稱:嶺東科技大學
系所名稱:財務金融研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:英文
論文頁數:109
中文關鍵詞:灰色理論趨勢灰粗集合灰預測K-means分群巴菲特投資法則期貨期貨避險動態避險投資組合Sharpe指標VaR風險值
外文關鍵詞:Grey TheoryTrend Rough Sets TheoryGrey PredictionK-means ClusteringBuffett Investment RulesFuturesFutures HedgeDyn
相關次數:
  • 被引用被引用:9
  • 點閱點閱:153
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
股票或期貨在股市單一投資時,所需面臨單一較大風險,如何降低風險,控制風險,風險愈低,獲利的機會相對愈高,問題是要如何降低風險呢?本論文結合股票與期貨雙邊操作,以不同的投資策略做投資績效評估,且克服投資者在股市天性和情緒上的反應,遵循一套系統走,建立一套標準操作程序,以作為投資策略的工具,華爾街操盤人的名言『Cut Your Losses Short & Let Profit Run』,希望大家都能在股市中成為市場贏家。

本論文結合廣義式粗集合模型(GRS Model)與變精度粗集合模型(VPRS Model),來解決傳統粗集合模型的侷限性與缺點,並配合類神經模糊理論(Neuro-fuzzy Theory)、灰色系統理論(Grey System Theory)與K-means數值轉換工具,建立動態廣義式變精度粗集合預測模型(Prediction Model of DGVPRS),作為股票篩選的投資策略工具。

本論文所提出的動態廣義式變精度粗集合預測模型在現貨與期貨組合投資之策略包括四個步驟,第一步是證劵與市場分析,我們藉此評估所有可能投資工具的風險與預期報酬特性。第二步為是運用期貨合約來防備價格波動的風險。第三步為加入風險值,有效的控管風險,使報酬率達到最大。第四步為設立停損點且使用Sharpe指標評估投資組合投資績效。

本論文使用多組不同的投資組合策略,投資報酬率及績效評估不管是在現貨、現貨搭大台期、現貨搭小台期績效皆優於大盤報酬率與績效評估,且現貨搭大台期投資組合績效最佳,故本模型為投資績效遠遠優於大盤,不管是在現貨搭小台期或現貨搭大台期平均都有30%的年投資報酬率。此外本論文加入變異數-共變異數法風險值,可以讓投資者清楚知道,他們所投入的資金所需承擔最大的風險。
Any investment strategy in stock markets with either single one of both stocks or futures will definitely face higher risk. How to reduce and control investment risk will be the critical issue. Whenever the risk is reduced, the profit probabilities will be naturally increased relatively. This thesis is combined with bilateral operation on both stocks and futures. The investment performance will be evaluated by means of various investment strategies. Also, the psychologically emotional response of investors in stock markets actually follows a set of system. They create a set of standard operational procedures to act as the tools for mapping investment strategies. There runs a well-known saying among the fund investing managers at the Wall Street and it says: “Cut Your Losses Short and Let Profit Run". The author sincerely hopes every investor can become a winner in stock markets.

This thesis is combined with GRS Model and VPRS Model to solve the problematic limitation and defects in traditional Rough Set Models. It is also integrated with Neuro-fuzzy Theory, Grey System Theory and K-means clustering to create the Prediction Model of DGVPRS to act as the investing strategies for stock screening selection.

The Prediction Model of DGVPRS proposed in this thesis includes 4 steps in the investigate strategies of the combinations in stocks and futures. Step 1 means the analysis for securities and markets. By means of this, we can evaluate the characteristics of risk and predicted return for all possible investing kits. Step 2 means the prevention against risk of fluctuating stock prices by using futures contracts. Step 3 means the adding risk values to effectively control risk with the maximum ROR (rates of returns) reached. Step 4 means the setting for stop-loss points and it is also vested with the Sharpe Indicators to evaluate the performance of investment portfolio.

This thesis is designed with the investing strategies by using numerous investment portfolios. No matter in stocks, stocks-n-TAIEX Future and stocks-n-MiNi TAIEX Future, both ROR and performance were better than the public market. Also, the investment portfolios of stock-n-TAIEX Future reached the best performance. Thus, the investment performance for this model is far better than the public market. No matter in the investment portfolios of stock-n-MiNi TAIEX Future or stock-n-TAIEX, there were 30% ROR reached on the average. In addition, this thesis is also designed with Variance-Covariance VaR available for readers to clearly see the maximum potential risk for the fund they invested.
_________________________________________________________________________
Contents
Chinese Abstract…………………………………………………………….. …………..i
English Abstract…………………………………………………………….. …………..ii
Acknowledgements……………………………………………………………………….iv
Contents…………………………………………….….………………………………… v
List of Tables…………………………………………………………….………………vii
List of Figures………………………………………………………………………….....ix
Chapter 1 Introduction 1
1.1  Research Background 1
1.2  Research Motivation and Purposes 3
1.3  Research Objects and Limitations 5
1.4 The Structure of the Report 7
Chapter 2 Literature Reviews 9
Chapter 3 Research Theory………………………………………………………….20
3.1 The Generation of the Rough Set Theory and Application Background 21
3.2 The Grey Relation 31
3.3 Futures Hedge 33
Chapter 4  Research Model and Portfolio Strategy 40
4.1 Investment Theory 40
4.2 Investment Strategy 44
4.3 Volume and Price Analysis 46
4.4 Operating Rule 49
4.5 Stock and Futures Investment Strategy Models & Fund Allocation 51
Chapter 5  Experimental Result & Analysis 57
5.1 The Explanation for the Selection of Experimental Data and Attribute Decision 58
5.2 The Explanation on Experimental Steps 61
5.3 Investing Period & the Performance of Fund Allocation for Portfolios 72
Chapter 6  Conclusion and Suggestion 81
6.1 Conclusion 81
6.2 Research Suggestion 82
References…………………………..…………………………………………………… 83
Appendix A、Performance for Simulated Portfolio Operating 2004~2006 …………88
Appendix B、Technical Indicator………………………………………….…………101
Appendix C、TAIEX Futures & Margining Table…………………………………. 106
二、English
[1] Alan C. Shapiro, Foundations of Multinational Financial Management, 2nd ed., Allyn and Bacon., 1994.
[2] Jeffrey Racine(2001) Nonlinear Predictability of Stock Returns
[3] Raymond at al(2001) Stock prediction using a neural oscillatory
[4] Charles P. Jones, Investments: Analysis and Management, 3rd ed., John Wiley & Sons, Inc., 1991.
[5] Edwin J. Elton and Martin J. Gruber, Modern Portfolio Theory and Investment Analysis, John Wiley and Sons, Inc., 1995.
[6] J. Deng, Control problems of grey system, Systems & Control Letters 1 (5) (1982) 288–294.
[7] C. Chen, T. Tien, A new transfer function model: the gray dynamic model GDM(2,2, 1), International Journal of Systems Science 27 (12) (1996) 1371–1379.
[8] Fama, E. F., “Efficient Capital Markets : A Review of Theory and Empirical Work,” Journal of Finance, May 1970, pp383~417.
[9] S.W. Hsiao, M.C. Liu, A morphing method for shape generation and image prediction in product design, Design Studies 23 (5) (2002) 533–556.
[10] C.I. Hsu, Y.H. Wen, Improved grey prediction model for trans-pacific air passenger market, Transportation Planning and Technology 22 (2) (1998) 87–107.
[11] L. Hsu, Applying the Grey prediction model to the global integrated circuit industry, Technological Forecasting and Social Change 70 (2003) 177–186.
[12] K. Le, Grey forecasting control: a new control scheme, Advanced Model Simulation 14 (2) (1988) 27–36.
[13] Anderberg, M.R., 1973. Cluster Analysis for Applications. Academic Press, London.
[14]Merton, Robert C., “An Analytic Derivation of the Cost of Deposit Insurance and Load Guarantees,An Application of Modern Option Pricing Theory,” Journal of Banking and Finance, 1977, pp.3~11.
[15] Dong,D., McAvoy, T.J., 1996. Nonlinear principal component analysis based on principal curves and neural networks. Comput. Chem. Eng. 20 (1), 65±78.
[16] Ting-Cheng Chang, Mei-Li You, Kun-Li Wen, Oct.1998, “The Study of Regression Based on Grey System Theory,” IEEE SMC’1998 Conference, pp.1842-1844.
[17] Julong Deng, 1989, “Introduction of Grey System Theory, ”Journal of Grey System, vol. 1, no. 1,pp.1-24
[18] Kun-Li Wen, etc., 2002, “Grey Prediction,” CWC publisher, Taipei, Taiwan.
[19] .Kun-Li Wen, etc., 2003, “Grey Relational,” Gauli publisher, Taipei, Taiwan.
[20] Yi-Fung Huang, Lian-Kai Wang & Kun-Li Wen,Dec. 2003, ”GM(1,1) Toolbox for ngineering,”The 8th National Conference of Grey Theory & Applications, C017.
[21] G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting & Control, New Jersey: Prentice-Hall, 1994.
[22] Ambrose, J.M., and Seward, J.A., 1988, Best’s ratings , Financial Ratios and Prior Probabilities in Insolvency Prediction, Journal of Risk and Insurance, 55, 2, 229-244.
[23] Brockett, P.L., Cooper, W.W., Golden, L.L., and Pitaktong, U., 1994, A Neural Network Method for Obtaining An Early Warning of Insurance Insolvency, Journal of Risk and Insurance, 61, 3, 402-424.
[24]Deng, J.L., 1982, The Control Problems of Grey Systems, Systems & Control Letters, 5, 288-94.
[25]Lee, S.H., and Urrutia, J.L., 1996, Analysis and Prediction of Insolvency in The Property-Liability Insurance Industry:A Comparison of Logit and Hazard Models, Journal of Risk and Insurance, 63, 1, 121-130.
[26] Sun, M., 1999, Grey Relational Analyzing The Influencing Factors of Economic Benefit in Hospital, Journal of Grey System, 11, 1, 53-59.
[27]Yu-Chen Tu, Chin-Tsai Lin, and Hsiang-Ju Tsai, 2001, The Performance Evaluation Model of Stock-Listed Banks in Taiwan:By Grey Relational Analysis and Factor Analysis, Journal of Grey System, 13, 2, 153-164.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 葉石濤(1993)。《臺灣文學史綱》。台北:文學界雜誌社
2. 葉石濤(1993)。《臺灣文學史綱》。台北:文學界雜誌社
3. 陳柔縉(2006)。〈摩登新世紀:日本領台後,臺灣的西方文明體驗〉,經典雜誌編,《臺灣人文四百年》,93,台北:經典雜誌。
4. 林麗雲(1999)。〈為臺灣傳播研究另闢蹊徑?傳播史研究與研究途徑〉。《新聞學研究》,63,35-54。
5. 陳柔縉(2006)。〈摩登新世紀:日本領台後,臺灣的西方文明體驗〉,經典雜誌編,《臺灣人文四百年》,93,台北:經典雜誌。
6. 林麗雲(1999)。〈為臺灣傳播研究另闢蹊徑?傳播史研究與研究途徑〉。《新聞學研究》,63,35-54。
7. 呂紹理(2002)。〈日治時期臺灣廣播工業與收音機市場的形成(1928-1945)〉。《國立政治大學歷史學報》,19:297-334。
8. 呂紹理(2002)。〈日治時期臺灣廣播工業與收音機市場的形成(1928-1945)〉。《國立政治大學歷史學報》,19:297-334。
9. 13. 蕭長瑞 (1997),銀行保管業務之範圍及其法律關係,財稅研究。
10. 13. 蕭長瑞 (1997),銀行保管業務之範圍及其法律關係,財稅研究。
11. 葉龍彥(1999)。〈臺北廣播電臺的建置-臺灣廣播之始〉。《臺北文獻直字》,130,87-118。
12. 葉龍彥(1999)。〈臺北廣播電臺的建置-臺灣廣播之始〉。《臺北文獻直字》,130,87-118。
13. 鄭自隆(1999)。〈廣告與臺灣社會:戰後五十年的變遷〉。《廣告學研究》,13,19-38。
14. 鄭自隆(1999)。〈廣告與臺灣社會:戰後五十年的變遷〉。《廣告學研究》,13,19-38。
15. 簡秀昭(2003)。〈不落男人後:愛國婦人會〉。載於林金田(主編),《烽火歲月—戰爭體制下的臺灣史料特展(上)》,頁137-150。南投:臺灣文獻館。