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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/141066


    Title: 隱藏式馬可夫狀態轉換模型下的動態資產配置
    Dynamic Asset Allocation under Hidden Markov Regime Switching Model
    Authors: 盧建豪
    Lu, Chien-Hou
    Contributors: 江彌修
    Chiang, Mi-Hsiu
    盧建豪
    Lu, Chien-Hou
    Keywords: 資產配置
    隱藏式馬可夫模型
    狀態轉換模型
    分層式風險平價
    Asset Allocation
    Hidden Markov Model
    Regime-switching Model
    Hierarchical Risk Parity
    Date: 2022
    Issue Date: 2022-08-01 17:30:05 (UTC+8)
    Abstract: 本文探討隱藏式馬可夫狀態轉換模型是否能夠使投資組合績效上升。基於隱
    藏式馬可夫模型對台灣加權指數進行狀態分類後，得到兩種狀態：高波動低報酬
    狀態與低波動高報酬狀態。本文建立逆變異數加權、分層式風險評價與二次規劃
    最小化變異數三個投資組合，並採用 2007 年 1 月 4 日至 2021 年 12 月 31 日的台灣股市資料與美債報酬進行回測。實證發現，狀態轉換下的動態資產配置能使投資組合的夏普比率、索提諾比率與最大策略虧損報酬上升，其中又以加入狀態轉換模型的逆變異數加權投資組合表現最佳。
    This paper explores whether a hidden Markov regime-switching model can improve portfolio performance. After we classify the Taiwan Weighted Index based on the Hidden Markov Model, two states are obtained: the state of high volatility and low return, and the state of low volatility and high return. This paper constructs three portfolios: inverse variance weighting, hierarchical risk parity and quadratic programming minimizing variance. We conduct backtests based on Taiwan stock market and U.S. bond data from January 4, 2007 to December 31, 2021. We find that
    the dynamic asset allocation under the regime-switching model can increase the Sharpe ratio, Sortino ratio and maximum drawdown return of the portfolio. The inverse
    variance weighted portfolio under the regime-switching model performs the best.
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    Description: 碩士
    國立政治大學
    金融學系
    109352027
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0109352027
    Data Type: thesis
    DOI: 10.6814/NCCU202200938
    Appears in Collections:[Department of Money and Banking] Theses

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