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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 洪一薰(I-Hsuan Hong) | |
dc.contributor.author | Tzu-Hao Lin | en |
dc.contributor.author | 林子皓 | zh_TW |
dc.date.accessioned | 2021-06-17T01:17:05Z | - |
dc.date.available | 2022-08-10 | |
dc.date.copyright | 2017-08-20 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-08-14 | |
dc.identifier.citation | Björk, T., Murgoci, A., & Zhou, X. Y. (2014). Mean–variance portfolio optimization with state‐dependent risk aversion. Mathematical Finance, 24(1), 1-24.
Cariño, D. R., & Turner, A. L. (1998). Multiperiod asset allocation with derivative assets. Worldwide asset and liability modeling, 10, 182. Campbell, R., Huisman, R., & Koedijk, K. (2001). Optimal portfolio selection in a Value-at-Risk framework. Journal of Banking & Finance, 25(9), 1789-1804. Dhar, V., & Stein, R. M. (2016). FinTech Platforms and Strategy. Evans, J. L. (2004). Wealthy investor attitudes, Expectations, and Behaviors toward risk and return. The Journal of Wealth Management, 7(1), 12-18. Jorion, P. (2000). Value at risk. Li, D., & Ng, W. L. (2000). Optimal dynamic portfolio selection: Multiperiod mean‐variance formulation. Mathematical Finance, 10(3), 387-406. Liu, Y., & Ralescu, D. A. (2017). Value-at-risk in uncertain random risk analysis. Information Sciences, 391, 1-8. Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.. Najafi, A. A., & Mushakhian, S. (2015). Multi-stage stochastic mean–semivariance–CVaR portfolio optimization under transaction costs. Applied Mathematics and Computation, 256, 445-458. Nicoletti, B. (2017). The Future of FinTech: Integrating Finance and Technology in Financial Services. Springer. Rockafellar, R. T., & Uryasev, S. (2000). Optimization of conditional value-at-risk. Journal of risk, 2, 21-42. Sharpe, W. F. (1994). The Sharpe Ratio. The journal of portfolio management, 21(1), 49-58. Vigna, E., & Haberman, S. (2001). Optimal investment strategy for defined contribution pension schemes. Insurance: Mathematics and Economics, 28(2), 233-262. 證券暨期貨月刊,2016。自動化投資理財顧問 ( Robo-Advisor ) 之發展第三 十四卷,第十期。 金融監督管理委員會,2015。打造數位化金融環境3.0全面啟動。 <http://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201501130003&toolsflag=Y&dtable=News>,上網日期 : 2017.07.11 科技政策觀點,2016。金融科技 ( Fintech ) 發展的國際趨勢我國的借鏡。 < https://portal.stpi.narl.org.tw/index/article/10254>,上網日期 : 2017.07.11 台灣證券交易所,2015。打造證券市場數位化環境之發展策略期末報告。 < http://www.tse.com.tw/ch/products/publication/download/0003000136.pdf>,上網日期 : 2017.07.11 Central Intelligence Agency,2016。Gross national saving。 < https://www.cia.gov/library/publications/the-world-factbook/rankorder/2260rank.html >,上網日期 : 2017.07.11 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/67007 | - |
dc.description.abstract | 資金如何配置在不同的資產在資金有限下一直是投資中重要的議題,多資產的多期資源配置問題,大多目標為如何使投資組合達到預期報酬最大化或最小化風險。不同的資產配置權重將影響投資組合的波動程度,投資高風險的資產雖能帶來增加預期報酬和高獲利的機會,但也會增加投資組合的變化程度,本研究考慮了投資者未來各期的消費,比起獲利投資者更在意資金出現不足的狀況,在單期挹注資金的方式下,與以往的研究不同之處在於以資金低於總消費折現的差額來衡量下半部風險,目標是最小化投資期間內的資金不足總額。
本研究使用動態規劃方法建立模型,選取金融市場的指數股票型基金當作投資標的物,以資產配置權重當決策變數,透過逆向歸納法求解,找出不同投資期間和不同總消費金額下的資產配置決策,讓投資者知道在面對不同的未來消費總額與投資期間該如何於現在規劃資金配置以達到最小化投資期間預期資金不足總額。 | zh_TW |
dc.description.abstract | How to distribute our money to different assets under the budget limit is an important issue in investment. Most of the objectives in multi-asset and multi-period resource allocation problem are maximize expected return or minimize portfolio risk. Different asset allocation weights will affect the volatility of the portfolio. Investing in high-risk assets will not only increase the expected return, but also the volatility of the portfolio. This study takes the future consumption into account and minimize the total amount of capital shortage during the investment period. We assume that investors are more concerned about capital shortage than the profit. This study use the margin between the total discounted consumption and the current wealth to measure the downside risk instead of portfolio’s standard deviation.
In this study, we establish a dynamic programming model and select the index stock funds in the financial market as the investment assets. We find out the asset allocation weight under different investment periods and different total consumption to minimize the expected total amount of capital shortage during the investment period by backward induction. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T01:17:05Z (GMT). No. of bitstreams: 1 ntu-106-R04546034-1.pdf: 1502853 bytes, checksum: c8258ee22eb54d6bef17da8be6419127 (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | 口試委員審定書 ii
誌謝 iii 中文摘要 iv Abstract v 目錄 vi 圖目錄 vii 表目錄 viii 第一章 緒論 1 第二章 多期動態資產配置模型 7 2.1問題描述 7 2.2逆向歸納法求解動態規劃模型 9 2.2.1動態規劃求解過程 9 2.2.2模型規劃過程 10 第三章 數值分析 16 3.1 投資年限長短的影響 16 3.2 消費總額的影響 22 第四章 結論 25 Reference 27 | |
dc.language.iso | zh-TW | |
dc.title | 考慮多期消費及減少資金不足之資產配置研究 | zh_TW |
dc.title | Asset allocation in multi-period consumption to avoid
capital shortage | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳吉政(CHI-CHENG WU),李家岩(Chia-Yen Lee),陳文智(Wen-Chih Chen) | |
dc.subject.keyword | 動態規劃,資產配置,多期消費,資金不足,下方風險,風險管理, | zh_TW |
dc.subject.keyword | Dynamic programing,Assets allocation,Multi-period consumption,Capital shortage,Downside risk,Risk Management, | en |
dc.relation.page | 29 | |
dc.identifier.doi | 10.6342/NTU201702995 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2017-08-14 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
顯示於系所單位: | 工業工程學研究所 |
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