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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 曹承礎 | |
| dc.contributor.author | Yu-Che Cheng | en |
| dc.contributor.author | 鄭育哲 | zh_TW |
| dc.date.accessioned | 2021-06-17T00:50:16Z | - |
| dc.date.available | 2020-02-10 | |
| dc.date.copyright | 2020-02-10 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-02-04 | |
| dc.identifier.citation | 天下雜誌. (2019). 聯發科做對這3件事. Retrieved from https://www.cw.com.tw/article/article.action?id=5096914
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/66671 | - |
| dc.description.abstract | With exponential increase of computing power and data generated, Artificial Intelligence (AI) is expected to thrive and drives the next wave of productivity improvement and business innovation. Investors who want to bet on companies that can benefit from this trend are wise to do solid researches and have a well-diversified portfolio first, as nothing is for certain and investing is about managing risks. This thesis walks through these processes for typical retail investors with limited resources. Using Exchange Trade Funds (ETF) accessible to retail investors, we statistically allocate asset (SAA) to construct diversified portfolio, tactically adjust allocation (TAA) depending on where we are in the economic cycle, and dynamically adjust allocation (DAA) to manage extreme risk scenario like recession. Stressing on that one should only invest in businesses they understand, we case study two publicly traded companies participating at two ends of the AI value chain. On the cloud side, we look at US e-commerce giant, Amazon, and on the edge side, we look at Taiwan’s top IC supplier, MediaTek. Methods of study include industry and competitive analysis for business overview, operation efficiency and moat analysis for past profitability, financial ratios for current health, and future growth and overall valuation. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T00:50:16Z (GMT). No. of bitstreams: 1 ntu-109-R03749026-1.pdf: 24773344 bytes, checksum: f3cc8ec1190c1ac7a12a58b7c167ed22 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | Abstract .......................................................................................................................ii
List of Figures ............................................................................................................ v Chapter 1: Introduction ...............................................................................................1 1.1 Who are Retail Investors? .....................................................................................1 1.2 What is AI and Why Invest in It? ...........................................................................2 1.3 Thesis Layout – Where, When and How .............................................................. 5 Chapter 2: Investment Theory Review ........................................................................ 6 2.1 Efficient Market Hypothesis .................................................................................. 6 2.2 Behavioral Finance .............................................................................................. 9 2.3 Adaptive Market Hypothesis ................................................................................. 12 Chapter 3: Portfolio Construction to Follow Beta ....................................................... 13 3.1 Statistical Asset Allocation ................................................................................... 13 3.2 Tactical Asset Allocation ....................................................................................... 18 3.3 Dynamic Asset Allocation .................................................................................... 22 Chapter 4: AI Stock Analysis to Seek Alpha ............................................................... 25 4.1 Analysis Checklist ............................................................................................... 25 4.2 Data Sources ....................................................................................................... 28 4.3 Machine Learning ............................................................................................... 29 4.4 Case Study: Amazon ........................................................................................... 32 4.4.1 Business Overview ...........................................................................................32 4.4.2 Operation Profitability ........................................................................................38 4.4.3 Financial Health ................................................................................................40 4.4.4 Valuation ...........................................................................................................42 4.4.5 Opportunity / Risks ............................................................................................44 4.5 Case Study: MediaTek ........................................................................................ 47 4.5.1 Business Overview ............................................................................................47 4.5.2 Operation Profitability .........................................................................................52 4.5.3 Financial Health ................................................................................................54 4.5.4 Valuation ...........................................................................................................56 4.5.5 Opportunity / Risks ............................................................................................59 Chapter 5: Conclusion ............................................................................................... 60 Reference .................................................................................................................. 61 Appendix I: Global Scales ......................................................................................... 64 Appendix II: Multi-Stage DCF Model ......................................................................... 71 Appendix III: iPhone Xs Bill of Materials .................................................................... 72 Appendix IV: 5G Primer ............................................................................................ 73 Appendix V: Financial History .................................................................................... 75 Appendix VI: Technical Analysis ................................................................................ 78 Appendix VII: Financial Statements Visualization ...................................................... 79 | |
| dc.language.iso | en | |
| dc.subject | 亞馬遜 | zh_TW |
| dc.subject | 投資組合 | zh_TW |
| dc.subject | 人工智能 | zh_TW |
| dc.subject | 股票分析 | zh_TW |
| dc.subject | 聯發科技 | zh_TW |
| dc.subject | ETF | en |
| dc.subject | Asset | en |
| dc.subject | Allocation | en |
| dc.subject | Stock | en |
| dc.subject | Analysis | en |
| dc.subject | Artificial | en |
| dc.subject | Intelligence | en |
| dc.subject | Retail | en |
| dc.subject | Investor | en |
| dc.subject | Case | en |
| dc.subject | Amazon | en |
| dc.subject | MediaTek | en |
| dc.subject | Portfolio | en |
| dc.subject | AI | en |
| dc.subject | SAA | en |
| dc.subject | TAA | en |
| dc.title | 投資組合與人工智能概念股票分析:以亞馬遜和聯發科技為例 | zh_TW |
| dc.title | Analysis of Retail Investor's Portfolio with AI Stocks: The Case of Amazon and MediaTek | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 謝冠雄,陳建錦 | |
| dc.subject.keyword | 投資組合,人工智能,股票分析,亞馬遜,聯發科技, | zh_TW |
| dc.subject.keyword | Portfolio,Asset,Allocation,Stock,Analysis,Artificial,Intelligence,Retail,Investor,Case,Amazon,MediaTek,ETF,AI,SAA,TAA, | en |
| dc.relation.page | 79 | |
| dc.identifier.doi | 10.6342/NTU202000014 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-02-05 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 企業管理碩士專班 | zh_TW |
| 顯示於系所單位： | 管理學院企業管理專班(Global MBA) | |
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|---|---|---|---|
| ntu-109-1.pdf 未授權公開取用 | 24.19 MB | Adobe PDF |
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