有鑒於過去因CPPI產品追高殺低的特性使得股市面臨大波動的情況，造成極大損失，本研究主要目的在於利用總體經濟指標與馬可夫轉換模型區分出不同市場狀態，依據各期狀態的轉換動態調整資產配置，建構出以狀態轉換為基礎的投資組合，接著，應用固定比例投資組合保險策略，調整各項參數設定，同時比較允許和不允許放空的情形以觀察策略績效表現差異。由於追求穩定收益是投資人的目標，因此，本研究並不是著重在策略應用是否能超越大盤績效，而是找到使投資組合績效持續且穩定地維持正報酬的策略應用。
本研究參考Kritzman, Page, and Turkington (2012)的做法，使用亞洲地區共8個國家2001年至2014年的股票債券季資料，以2001年第一季至2009年第四季作為起始估計樣本期間，各期增加樣本期間數以估計各期狀態變化。結果顯示經由狀態調整投資組合的績效表現優於等權重配置各國股債的組合，此外，在不允許放空的狀況下，狀態調整投資組合的績效表現亦是相對較佳。

The purpose of this paper is to use macroeconomic indicator and Markov switching model to distinguish different states of market and do dynamic asset allocation based on the transition between regimes to construct a regime-based portfolio. Subsequently, constant proportion portfolio insurance strategy is applied to the regime-based portfolio. Finally, we assume different scenarios to compare difference between these performances. We hope to find a strategy that can provide investors a sustained and stable performance.
This study refers to Kritzman, Page, and Turkington (2012). We use stock indices and bonds of eight countries in Asia to form our portfolio in the estimation period from 2001 to 2014 on a quarterly basis. The empirical results show that the performance of a regime-based portfolio dynamically adjusted is better than EW, an equal weighted portfolio. In addition, regime-based portfolios perform relatively better than EW in the situation of not allowing selling short.

論文審定書 i
誌謝 ii
摘要 iii
ABSTRACT iv
I. INTRODUCTION 1
1.1 Background Information 1
1.2 Research Purpose 3
1.3 Research Structure 4
II. LITERATURE REVIEW 5
2.1 Markov Switching Model 5
2.2 Portfolio Insurance Strategy 10
III. METHODOLOGY 12
3.1 Data Description 12
3.2 Hidden Markov Switching Model 14
3.2.1 Introduction 14
3.2.2 Markov Chain 15
3.3 Regime-based Portfolio Construction 16
3.3.1 Regime Estimation 17
3.3.2 Weight Allocation 23
3.4 Portfolio Insurance Strategy 24
3.5 Performance Measures 25
3.5.1 Sharpe Ratio 25
3.5.2 Information Ratio 26
IV. EMPIRICAL RESULTS 27
4.1 Data 27
4.2 The Performance of Regime-Based Portfolios 28
4.2.1 Weight Allocation 28
4.2.2 Comparison of Results 34
4.3 Portfolio Insurance Strategy 37
V. CONCLUSION 43
5.1 Conclusion 43
5.2 Recommendations for Further Research 46
REFERENCES 47

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