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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 崔茂培 | zh_TW |
| dc.contributor.advisor | Mao-Pei Tsui | en |
| dc.contributor.author | 王姿云 | zh_TW |
| dc.contributor.author | Zih-Yun Wang | en |
| dc.date.accessioned | 2023-12-20T16:18:56Z | - |
| dc.date.available | 2023-12-21 | - |
| dc.date.copyright | 2023-12-20 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-09-12 | - |
| dc.identifier.citation | G. Marti, F. Nielsen, M. Bińkowski, and P. Donnat, “A review of two decades of correlations, hierarchies, networks and clustering in fnancial markets,” pp. 245–274, 03 2021.
F. Ren, Y.-N. Lu, S.-P. Li, X.-F. Jiang, L.-X. Zhong, and Tian, “Dynamic portfolio strategy using clustering approach,” PLOS ONE, vol. 12, no. 1, pp. 25–31, Jul. 2017. [Online]. Available: https://doi.org/10.1371/journal.pone.0169299 P. C. K. M. Elias Mwakilama, Patrick Ali and L. Eneya, On Average Distance of Neighborhood Graphs and Its Applications. IntechOpen, 2021. Y. Bengio, O. Delalleau, N. Roux, J.-F. Paiement, P. Vincent, and M. Ouimet, “Spectral dimensionality reduction,” CIRANO, CIRANO Working Papers, vol. 207, 01 2004. R. Korajczyk and G. Connor, “Performance measurement with the arbitrage pricing theory: A new framework for analysis,” Journal of Financial Economics, vol. 15, pp. 373–394, 03 1986. 臺灣證券交易所與富時國際有限公司,“臺灣50指數編製說明,” 2002. [Online]. Available: https://www.taiwanindex.com.tw/files/indexfile/1477467076.pdf (Accessed on: 2022/10/25). F. Russell and the Taiwan Stock Exchange, “Ftse twse taiwan index series,” 2022. [Online]. Available: https://research.ftserussell.com/products/downloads/FTSET WSET aiwanI ndexSeries.pdf (Accessed on: 2022/10/25). TWSE, “Daily trading value/volume of individual securities,” 2022.[Online]. Available: https://www.twse.com.tw/en/trading/historical/stock-day.html (Accessed on: 2022/10/25). FinMind, “Daily trading value/volume of individual stocks,” 2020. [Online]. Available: https://finmindtrade.com/ (Accessed on: 2022/10/25). H. Markowitz, “Portfolio selection,” The Journal of Finance, vol. 7, no. 1, pp. 77–91, 1952. [Online]. Available: http://www.jstor.org/stable/2975974 A. Fernández and S. Gómez, “Portfolio selection using neural networks,” Computers Operations Research, vol. 34, no. 4, pp. 1177–1191, 2007. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0305054805002042 Y. Chen, S. Mabu, and K. Hirasawa, “A model of portfolio optimization using time adapting genetic network programming,” Computers Operations Research, vol. 37, pp. 1697–1707, 10 2010. Y. Chen, E. Ohkawa, S. Mabu, K. Shimada, and K. Hirasawa, “A portfolio optimization model using genetic network programming with control nodes,”Expert Systems with Applications, vol. 36, pp. 10 735–10 745, 09 2009. A. Nazemi, B. Abbasi, and F. Omidi, “Solving portfolio selection models with uncertain returns using an artifcial neural network scheme,” Applied Intelligence, 10 2014. P.-C. Ko and P.-C. Lin, “Resource allocation neural network in portfolio selection,” Expert Systems with Applications, vol. 35, pp. 330–337, 07 2008. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91285 | - |
| dc.description.abstract | 對於初學投資的人來說，這項研究提供了一種實用的方法，來將特定產業的股票進行分類。這有助於更輕鬆地追踪台灣的新興領域，並簡化了投資流程。此外，我們還提供了在牛市和熊市中的投資策略。
我們使用股票收盤價的對數差來計算相關係數。這個方法使我們能夠識別出一個最小生成樹，用於進行分類。此外，相關係數矩陣還幫助我們提取特徵值和特徵向量，這對於進行擴散映射降維分析非常有用。這有助於優化投資者的投資策略。 這項研究中的分類方法與實際情況非常相符。所提供的股票投資策略在牛市和熊市中的表現都比隨機從每個行業中選擇股票要獲得更好的利潤。這些分類和策略方法都可以有效應用於台灣的市場環境中。 | zh_TW |
| dc.description.abstract | For novice investors, this study provides a method to classify stocks of certain industries to track emerging industries easily in Taiwan, which makes people invest conveniently. And, we also provide a strategy to invest stocks in bull market and bear market.
We use logarithm difference of stocks’ closing prices to calculate the correlation coefficient. Hence, we can find a minimum spanning tree to classify. Moreover, the correlation coefficient constructs a matrix to find eigenvalues and eigenvectors, which can be used diffusion map to analyze them and it can adjust investors’ strategy of investment. The classification is close to the actual situation, and the strategy of the stock method provides a better return than choosing one stock from each industry randomly in bull market or bear market. The method of classification and strategy can be used in the Taiwan market. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-12-20T16:18:55Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-12-20T16:18:56Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgements iii
摘要 v Abstract vii Contents ix List of Figures xiii List of Tables xv Chapter 1 Introduction 1 Chapter 2 Literature review. 3 2.1 Preliminary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 2.1.1 Correlation Coefficient . . . . . . . . . . . . . . . . . . . . . . .3 2.1.2 Minimum Spanning Tree . . . . . . . . . . . . . . . . . . . . . .7 2.1.3 Kruskal’s Algorithm . . . . . . . . . . . . . . . . . . . . . . . .8 2.1.4 Ultrametric Spaces . . . . . . . . . . . . . . . . . . . . . . . . .9 2.1.5 Diffusion Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2 Taiwan Stock Market . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.2.1 Exchange-traded Funds . . . . . . . . . . . . . . . . . . . . . . . 25 2.2.2 FTSE TWSE Taiwan 50 Index . . . . . . . . . . . . . . . . . . . 25 2.2.3 Constituent Selection Criteria . . . . . . . . . . . . . . . . . . . 26 2.2.4 Constituent Adjustment . . . . . . . . . . . . . . . . . . . . . . 27 2.2.5 Yuanta/P-shares Taiwan Top 50 ETF . . . . . . . . . . . . . . . 27 Chapter 3 The selection of portfolio 29 3.1 Centrality or Peripherality in Portfolio . . . . . . . . . . . . . . . 29 3.2 Central Portfolio and Peripheral Portfolio . . . . . . . . . . . . . 30 3.3 Data Collection Procedure . . . . . . . . . . . . . . . . . . . . . . 31 Chapter 4 Market Conditions 33 4.1 Identifcation of Market Conditions . . . . . . . . . . . . . . . . . 33 4.2 Market Situation Analysis . . . . . . . . . . . . . . . . . . . . . . 35 4.3 Selection Horizon and Investment Horizon . . . . . . . . . . . . . 37 4.4 Return on Investment . . . . . . . . . . . . . . . . . . . . . . . . 39 Chapter 5 Research Results 41 5.1 Investment Strategy . . . . . . . . . . . . . . . . . . . . . . . . . 41 5.2 Classifcation of Stocks on Difusion Map . . . . . . . . . . . . . . 43 Chapter 6 Conclusion 47 References 51 Appendix A — Criteria for Selecting Constituent Stocks for the Yuanta Taiwan 50 Index 55 A.0.1 Index Compilation . . . . . . . . . . . . . . . . . . . . . . . . . 55 A.0.2 Calculation Method . . . . . . . . . . . . . . . . . . . . . . . . . 55 A.1 Qualifcation Criteria and Selection Criteria of Constituent Stocks 57 A.1.1 Market Capitalization . . . . . . . . . . . . . . . . . . . . . . . 57 A.1.2 Free Float . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 A.1.3 Liquidity Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 A.2 Constituent Review and Weight Adjustment . . . . . . . . . . . . 60 A.2.1 Regular Review . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 A.2.2 Non-Regular Review . . . . . . . . . . . . . . . . . . . . . . . . 60 A.2.3 Weight Adjustment . . . . . . . . . . . . . . . . . . . . . . . . . 62 Appendix B — Central Portfolio and Peripheral Portfolio 65 | - |
| dc.language.iso | en | - |
| dc.subject | 投資策略 | zh_TW |
| dc.subject | 相關係數 | zh_TW |
| dc.subject | 股票標的分類 | zh_TW |
| dc.subject | 最小生成樹 | zh_TW |
| dc.subject | 擴散映射 | zh_TW |
| dc.subject | 股票標的分類 | zh_TW |
| dc.subject | 投資標的 | zh_TW |
| dc.subject | 投資策略 | zh_TW |
| dc.subject | 相關係數 | zh_TW |
| dc.subject | 最小生成樹 | zh_TW |
| dc.subject | 投資標的 | zh_TW |
| dc.subject | 擴散映射 | zh_TW |
| dc.subject | Diffusion Map | en |
| dc.subject | Financial Classification | en |
| dc.subject | Investment Objective | en |
| dc.subject | Investment Strategy | en |
| dc.subject | Correlation Coefficient | en |
| dc.subject | Minimum Spanning Tree | en |
| dc.subject | Diffusion Map | en |
| dc.subject | Financial Classification | en |
| dc.subject | Investment Objective | en |
| dc.subject | Investment Strategy | en |
| dc.subject | Correlation Coefficient | en |
| dc.subject | Minimum Spanning Tree | en |
| dc.title | 相關係數、最小生成樹、擴散映射，在投資標的分類和投資策略的應用 | zh_TW |
| dc.title | Application of Correlation Coefficient, MST and Diffusion Map in investment objectives classification and investment strategy | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 林澤佑;楊鈞澔 | zh_TW |
| dc.contributor.oralexamcommittee | Tse-Yu Lin;Chun-Hao Yang | en |
| dc.subject.keyword | 股票標的分類,投資標的,投資策略,相關係數,最小生成樹,擴散映射, | zh_TW |
| dc.subject.keyword | Financial Classification,Investment Objective,Investment Strategy,Correlation Coefficient,Minimum Spanning Tree,Diffusion Map, | en |
| dc.relation.page | 68 | - |
| dc.identifier.doi | 10.6342/NTU202304202 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2023-09-13 | - |
| dc.contributor.author-college | 理學院 | - |
| dc.contributor.author-dept | 應用數學科學研究所 | - |
| 顯示於系所單位： | 應用數學科學研究所 | |
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