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    Title: 如何選擇最佳的 ETF 投資組合模型: 以大中華地區的 ETF 為例
    How to choose the best ETF portfolio model: Take the Greater China ETFs as an example
    Authors: 黃彬怡
    Huang, Bin-Yi
    Contributors: 林建秀
    Lin, Chien-Hsiu
    黃彬怡
    Huang, Bin-Yi
    Keywords: 交易所買賣基金
    投資組合
    最大分散化投資組合模型
    風險平價投資組合模型
    ETF portfolio
    Maximum diversification portfolio
    Risk parity
    Date: 2021
    Issue Date: 2021-08-04 14:52:26 (UTC+8)
    Abstract: 目前金融市場的投資工具日趨多元化和複雜化,交易所買賣基金(Exchange Traded Fund,ETF)作為一種被動追求指數績效的基金,有較高的流動性、較低 的管理費和交易費用。同時,ETF 又能規避一些共同基金經理人的主觀錯誤。 交易股票型和債券型 ETF 時,就是同時交易一籃子金融商品,能分散風險,且 價值不容易大幅波動。這些優點使得投資人對 ETF 青睞有加。
    那如何投資 ETF 才能獲得更好的績效呢?這是每個投資者思考的問 題。本研究結合量化投資和現代投資組合理論(Modern Portfolio Theory),探討 以 ETF 為投資標的的各種投資組合模型的優劣,並進一步思考是否已經有著風 險分散化效果的 ETF 還需通過投資組合進一步控制風險。由於投資人有進鄉偏 誤(Home bias),本研究的資產標的都為大中華地區的 ETF,分別為華泰柏瑞滬 深 300 基金、元大台灣卓越 50 基金、恒生指數上市基金、恒生中國企業指數上市基金、國泰上証 5 年期國債基金和 ABF 香港創富債券指數基金。
    實證結果如下:(1)使用最小變異數、最大分散化和風險平價等以風險 為導向的投資組合模型時,可能會過度地依賴低風險資產,導致過多地犧牲了 上漲的潛能來換取控制風險的能力;(2)風險平價投資組合模型平均地分配風 險,對降低資產地集中程度和保留一部分的獲取報酬的能力有一定的作用;(3) 天真的分散化(Naïve Diversification)即等權重加權投資組合模型也有可取之處, 能保留部分收益,邏輯簡單且清晰,但是在不能抵禦外部衝擊;(4)最大夏普比 率投資組合模型同時考慮了收益和風險,但是該模型需要頻繁地進行調整權重 的特點會產生的交易費用和税,極大可能會侵蝕掉該投資組合的報酬;(5)一些好的 ETF 已經擁有分散化風險的投資指數,在風險和報酬方面取得了較好的平衡,因此無需再建構投資組合。因此,投資人在構建 ETF 的投資組合時,須足 夠 ETF 所追蹤指數的特徵,同時考慮投資組合模型的收益與風險目標。
    At present, investment tools in the financial market are becoming various and complicated. Exchange Traded Fund (ETF), as a fund that passively pursues index performance, has higher liquidity, lower management fees and transaction costs. At the same time, ETFs can avoid the subjective error of mutual fund managers. When trading stock-type and bond-type ETFs, it is same to trade a basket of financial products, which can diversify risks and is not prone to large fluctuations in value. These advantages make investors favor ETFs.
    So how to invest in ETFs to get better performance? This is a question that every investor is curious about. This research combines quantitative investment and Modern Portfolio Theory to explore the pros and cons of various portfolio models that use ETFs as investment targets, and further consider whether ETFs that already have risk diversification effects need to further control risks through portfolios models. Due to the home bias of many investors, the target assets of this study are all ETFs in the Greater China region, namely Huatai-PB CSI 300 ETF, Yuanta/P-shares Taiwan Top 50 ETF, Hang Seng Index ETF, Hang Seng China Enterprises Index ETF, Guotai SSE Delivrb 5 Yr Trs Bd Idx ETF and ABF Hong Kong Bond Index Fund.
    The empirical results are as follows: (1) When using risk-oriented portfolio models such as minimum variance, maximum diversification, and risk parity, it may be overly dependent on low-risk assets, resulting in excessive sacrifice of upside potential in exchange for risk control (2) The risk parity portfolio model distributes risks equally, which has a certain effect on reducing the concentration of assets and retaining a part of the ability to obtain rewards; (3) Equally weighted model, which is also called Naïve Diversification has merits. It can retain part of the upward potential. The logic is simple and clear for investors, but it cannot withstand external shocks; (4) The maximum Sharpe ratio portfolio model considers both returns and risks, but the model requires frequent adjustment of weights. The transaction costs and taxes generated by the characteristics of the model may greatly erode the return of the portfolio; (5) Some good ETFs already have tracked indexes with diversified risks, and achieved a good balance between risk and return. Therefore, there is no need to construct a portfolio anymore. Therefore, when investors construct an ETF portfolio, they must take into account the characteristics of the index tracked by the ETFs, while taking into account the return and risk objective of the investment portfolio model.
    Reference: Anderson, R. M., Bianchi, S. W. and Goldberg, L. R., (2012). “Will my risk parity strategy outperform?”, Financial Analysts Journal 68 (6), 75-93.
    Ardia, D. and Boudt, K., (2015). “Implied expected returns and the choice of a mean-variance efficient portfolio proxy.”, The Journal of Portfolio Management 41 (4), 68-81.
    Bruder, B. and Roncalli, T., (2012). “Managing risk exposures using the risk budgeting approach.”, Lyxor Asset Management, Paris.
    Callan Investments Institute, (2010). “The risk parity approach to asset allocation.”, Callan Associates.
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    Chaves, D., Hsu, J., Li, F. and Shakernia, O., (2011). “Risk parity portfolio vs. other asset allocation heuristic portfolios.”, The Journal of Investing 20 (1), 108-118.
    Choueifaty, Y., Coignard, Y., (2008). “Toward Maximum Diversification.”, Journal of Portfolio Management, vol. 35, 40-51, October.
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    Description: 碩士
    國立政治大學
    金融學系
    108352035
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0108352035
    Data Type: thesis
    DOI: 10.6814/NCCU202100701
    Appears in Collections:[Department of Money and Banking] Theses

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