歷經2008年的全球金融危機後，許多資產配置的學術論文研究裡，開始著重於風險配置，而不以未來報酬為依據，且資產配置的型態逐漸由靜態轉移至動態調整。本研究的目的為確認台灣市場是否能有效地利用管理波動度動態調整方式來控制其投資組合之波動度。
本研究使用Dopfel and Ramkumar (2013)的方法，透過歷史波動度計算出波動度臨界值，當作判斷月波動度為正常或高波動度的基準。將分類過後的月份，根據不同類型投資人會遇到的狀況，進行歷史資料的績效計算。再根據不同類型投資人的特性，進行資產權重的計算與分配，以建構投資組合，來確認管理波動度的投資組合是否有效。
實證結果顯示，此管理波動度的方法應用於台灣市場上，是能有效的控制其投資組合的波動度。而其中移動(滾動)視窗加上擴大視窗，且波動度臨界值設定為第85分位數的方法，其管理波動度的效果較佳。

After the Global Financial Crisis in 2008, many academic research papers on asset allocation began to focus on the risk of asset allocation, not on the return of a portfolio. The pattern of asset allocation has gradually shifted from static to dynamic adjustment. The purpose of this study is to determine whether the Taiwan market can effectively use dynamic adjustment of managed volatility to control the volatility of a portfolio.
The study is based on the research of Dopfel and Ramkumar (2013). First, we calculate the volatility cutoff, and classify the monthly volatility of the risky asset as normal volatility or high volatility by using a volatility cutoff. Second, according to different investors, we calculate the performance of different volatility regime transitions using historical data. Third, we calculate the holdings of the risky asset for different investors to construct our portfolios. Finally, we use different portfolios to determine whether the managed volatility portfolio is valid.
The empirical results show that the methodology of managed volatility effectively controls the volatility of portfolios in Taiwan. A methodology that uses a rolling window plus expanding window and assumes an 85th percentile volatility cutoff performs well in Taiwan.

摘要 I
ABSTRACT II
List of Tables IV
List of Figures VI
I. INTRODUCTION 1
1.1 General Background Information 1
1.2 Research Purpose 2
1.3 Overview 3
II. LITERATURE REVIEW 5
2.1 Asset Allocation 5
2.2 Dynamic Asset Allocation 7
2.3 Managed Volatility 10
III. DATA & METHODOLOGY 12
3.1 Data Description 12
3.2 Process of Methodology 12
3.3 Difference in Investors 12
3.4 Volatility Calculation & Volatility Regime Classification 14
3.5 Regime Transition Performance 15
3.6 Calculation and Transformation of Weight 19
3.7 Methodology of Parameter Calculation 23
IV. EMPIRICAL RESULTS 27
4.1 The Performance of Different Types of Investors 27
4.2 Performance during Financial Crisis 28
4.3 Comparison Between Investors 31
V. CONCLUSION 39
REFERENCES 43
APPENDIX 47

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