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研究生:李威成
研究生(外文):Li, WeiCheng
論文名稱:應用高階模糊派翠網路於股票市場之投資決策
論文名稱(外文):Application of High-Level Fuzzy Petri Nets to Investment Decisions of Stock Market
指導教授:沈榮麟沈榮麟引用關係
指導教授(外文):Victor R. L. Shen
口試委員:張仁俊洪偉文楊政穎賴阿福
口試日期:2012-07-24
學位類別:碩士
校院名稱:國立臺北大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:80
中文關鍵詞:金融市場投資理財支撐向量迴歸技術分析高階模糊派翠網路
外文關鍵詞:Financial MarketFinancial InvestmentSupport Vector RegressionTechnical AnalysisHigh-Level Fuzzy Petri Net
相關次數:
  • 被引用被引用:1
  • 點閱點閱:248
  • 評分評分:
  • 下載下載:15
  • 收藏至我的研究室書目清單書目收藏:1
近年來,由於資訊科技日益成長,且臺灣的金融市場相當活絡,使得投資理財風氣非常盛行。為促使資訊科技發展速度提升且兼顧金融市場發展趨勢,各種結合資訊科技技術於投資理財的電腦化系統也不斷推陳出新。本研究使用支撐向量迴歸(Support Vector Regression)對台灣的股票價格分別用天數及實際價格當做輸入資料來實作曲線近似的模擬,再用從學習中產生的模組對未來的股價走勢做預測分析及技術分析,並繪出趨勢圖。最後根據高階模糊派翠網路(High-Level Fuzzy Petri Net)來模組化投資理財的商業行為以發展較佳的投資決策,讓一般投資者能運用此系統了解未來的投資趨勢或走向。藉此,以全方位的財富管理系統,來提高個人理財的投資效益,幫助投資者能達到預期的個人理財目標,進而改善經濟狀況。
As information technology grows dramatically and the financial market in Taiwan turns out to be active, the investment management becomes very popular in the recent years. To facilitate the rapid development of information technology and the financial market, the application of information technology to financial investment becomes an important issue as essential evaluation metrics. In this thesis, we used a support vector regression machine for stock price in Taiwan, by inputting the data of daily and practical prices to implement approximate trend simulations and predictions. Then, we used the learned model data from the generated future stock price trends to analyze predictions and technical indices, and draw the trend diagram. Finally, we focus on modeling the business behavior of financial investment systems by the high-level fuzzy Petri net (HLFPN) for the purpose of developing an appropriate investment decision. Based on the HLFPN model, the proposed system provides individual investors to obtain relevant information to understand the investment trend. As a result, we proposed a practical financial investment system to enhance investment benefits and to help investors achieve the desired goals so as to improve the economy.
Acknowledgements Ⅰ
Abstract (Chinese) Ⅱ
Abstract (English) Ⅲ
Table of Contents Ⅴ
List of Figures Ⅶ
List of Tables Ⅷ

Chapter 1 Introduction 1
1-1 Motivation and Purposes 1
1-2 Thesis Organization 3

Chapter 2 Literature Review 4
2-1 Support Vector Machine 4
2-1-1 Support Vector Regression 4
2-2 Technical Analysis 7
2-2-1 Williams Index 8
2-2-2 Relative Strength Index 8
2-2-3 Psychological Line 9
2-3 High-Level Fuzzy Petri Net 10
2-2-3 Definitions 11
2-2-3 Fuzzy Reasoning 13
2-2-3 Fuzzy Reasoning Algorithm 16
2-4 Related Work 18

Chapter 3 The HLFPN-Based Investment Model 20
3-1 System Architecture 23
3-1-1 Architecture of SVR Model 24
3-1-2 Grid Search 24
3-2 The Definition of Membership Functions 25
3-3 Fuzzy Reasoning and Building HLFPN 28
3-4 Example of HLFPN in Fuzzy Reasoning 31
3-5 System Activity Diagram 36

Chapter 4 Experimental Results 41
4-1 The Research Scope and Limitation 41
4-1-1 The Research Scope 41
4-1-2 The Research Limitation 42
4-2 Stock Prediction 43
4-2-1 Estimation Method 43
4-2-2 Experimental Analysis 43
4-3 Investment Decision 51
4-3-1 The Performance of System Decision for One Year 51
4-3-2 The Performance of System Decision for Six Months 53
4-3-3 The Information of System Decision Process 55

Chapter 5 Conclusions and Future Work 61

References 63

Appendix 67
Code of Sub-Program Finding Investment Decision 67
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