應用時間序列ARMA模型於資産配置之研究

A Study of Applying Time Series ARMA Model to Asset Allocation

10.29973/JCSA.200503.0002

陳信宏(Hsin-Hung Chen)；韋伯韜(Duan Wei)；蔡憲唐(Hsien-Tang Tsai)；傳懷慧(Hwai-Hui Fu)

資産配置 ； 時間序列 ； 效率前緣 ； 平均數－變異數投資組合模型 ； Asset allocation ； time series ； efficient frontier ； Mean-Variance Portfolio Model

中國統計學報

43卷1期（2005 / 03 / 01）

15 - 31

繁體中文

過去應用馬可維茲平均數－變異數投資組合模型（MV模型）之相關研究，經常是依據過去的歷史資料分析投資工具的期望報酬與標準差，並假設這些投資工具未來的表現會與過去相同，而計算出效率前緣之投資組合。但事實上，過去的金融與經濟環境不一定能持續到未來，所以最佳資産與置的選擇雖可參考過去的經驗，但仍應對未來金融資産的報酬率做預測，並進行調整以降低資産配置決策偏誤的可能性。本文利用時間序列的ARMA模型對各項金融工具未來的報酬率先行預測，再利用每一季的預測結果計算最佳資産配置，建立動態資産配置模型。實證結果顯示，動態資産配置模型之獲利績效與穩定性明顯優於傳統MV模型所建立的靜態資産配置，其適用性也得到確認。

Over the past years, a considerable number of studies have been made on Markowitz Mean-Variance Portfolio Model (MV model). They usually estimated means and standard deviations of investment instruments' return rates by historical data, and assumed that the performance of these investment instruments in the future will be similar to that in the past to obtain the portfolios on the efficient frontier. In fact, the financial and economic environment may change in the future. Therefore, we should forecast the return rates of asset classes to reduce the bias of asset allocation decisions and acquire the optimal asset allocation. This article uses Time Series ARMA model to forecast the return rates of asset categories, and build up the dynamic asset allocation model to find the optimal asset allocation by the forecasting results. The empirical results show that the dynamic asset allocation model has better return and stability than traditional static asset allocation model. In addition, the usefulness of the dynamic asset allocation model is confirmed.

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