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https://ah.lib.nccu.edu.tw/handle/140.119/67100| 題名: | 馬可夫狀態轉換下最低條件風險值集中度投資組合之建構 On the Construction of Minimum CVaR Concentration Portfolios under Markovian Regime Shifts |
作者: | 賴韋志 | 貢獻者: | 江彌修 賴韋志 |
關鍵詞: | 最低條件風險值集中度投資組合 等值風險權重投資組合 馬可夫狀態 轉換模型 Risk Parity Portfolios Minimum CVaR Concentration Portfolios Markov regime-switching model |
日期: | 2013 | 上傳時間: | 1-Jul-2014 | 摘要: | 本文主要研究的投資組合策略為Boudt et al. (2013)所提出的最低條件風險值集中度(Minimum CVaR Concentration，簡稱MCC)投資組合，並且延伸Kritzman et al. (2012)以及Wang et al. (2012)將馬可夫狀態轉換模型應用於資產配置的方法，在市場狀態為狀態一(熊市)之下，將MCC投資組合下方風險控制在3.00%之下，建構一狀態相關(regime-dependent)MCC投資組合。\n 綜合本研究之實證結果，發現MCC投資組合在市場狀態為狀態一(熊市)之下，表現較狀態二(正常市場)差，主要原因為MCC投資組合在狀態一(熊市)時仍以達到均衡風險分散為主要目標，卻忽略了投資組合下方風險上升。而本研究所建構的狀態相關MCC投資組合，在熊市時的確能提升平均報酬率，而且降低平均報酬率的標準差、95%平均下方風險(CVaR)以及每月最大損失等風險。 The main portfolio strategy exploited in this paper is the Minimum CVaR Concentration (MCC) introduced by Boudt et al. (2013). Our paper is closely related to recent literature on drawing inference of asset allocation strategy from Markov regime-switching model, for instance, Kritzman et al. (2012) and Wang et al. (2012). We built a regime-dependent MCC portfolio under a bearish market condition by fixing the downside risk at a maximum of 3.00%. \n From the empirical evidence, we conclude that the main reason MCC portfolio performs better under normal market condition (condition 2) than under bearish market condition (condition 1) is because under condition 1, MCC portfolio strives to achieve risk diversification and ignores the increase of downside risk. While the regime-dependent MCC we propose can effectively increase average return, and lower average standard deviation, CVaR (95%), and biggest monthly loss. |
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資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0101352009 | 資料類型: | thesis |
| Appears in Collections: | 學位論文 |
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