本研究探討了大膽資產配置（Bold Asset Allocation, BAA）策略在中國、香港及台灣市場的應用和績效表現。通過對2006年6月至2023年12月期間的數據進行實證分析，結果顯示，BAA策略在大中華市場上展現出顯著的優勢，特別是在提高投資回報和控制風險方面。
研究首先對大中華市場的特殊性進行了深入探討，考量其市場結構、監管環境及經濟特點，並根據這些特點對BAA策略進行了適應性調整，選取了11種資產，包括股票ETF、REITs和債券ETF，組成進攻性、防禦性和保護性資產池。回溯期為12個月的歷史數據分析顯示，BAA-G4和BAA-G8/T2策略在不同市場條件下都表現出色，年化報酬率和波動度均優於富時大中華指數，並在最大回撤控制方面顯示出強大的抗跌能力。
此外，研究考慮了交易成本對策略績效的影響，結果顯示，儘管交易成本會降低策略的累積報酬率，但這些策略在考慮交易成本後，仍能提供較高的回報，顯示出其顯著的投資價值。研究還探討了定期定額投資法在不同策略下的應用，發現該方法能顯著降低策略的波動度，提升投資組合的穩定性。
本研究的主要貢獻在於驗證了BAA策略在大中華市場的適用性，展示了其在提升回報和控制風險方面的優勢，為投資者提供了一種新的資產配置策略選擇，特別是在不確定性高的市場環境下，BAA策略具有顯著的實踐價值和應用前景。然而，本研究也存在一些限制，如樣本期間較短、資產池選擇有限等，未來的研究可以通過延長樣本期間、增加資產池多樣性、優化交易成本模型以及引入更多風險管理指標等方法，進一步提升策略的穩定性和適用性，為投資者提供更全面和有效的資產配置建議。

This study investigates the application of the Bold Asset Allocation (BAA) strategy in the financial markets of China, Hong Kong, and Taiwan. Utilizing historical data from June 2006 to December 2023, the research adapts the BAA strategy by selecting 11 assets, including ETFs, REITs, and bond ETFs, organized into aggressive, defensive, and protective pools. The BAA strategy, integrating relative and absolute momentum principles, dynamically adjusts asset weights based on recent performance.
Empirical analysis reveals that the BAA-G4 and BAA-G8/T2 strategies significantly outperform traditional equal-weighted strategies and the FTSE Greater China Index. Specifically, these strategies achieve higher annualized returns, with the BAA-G4 and BAA-G8/T2 yielding 16.57% and 15.43% respectively, compared to the FTSE Greater China Index. They also exhibit lower volatility and better drawdown control, with maximum drawdowns of approximately 15%, compared to much higher drawdowns in the traditional strategies. Even after accounting for transaction costs, the BAA strategies maintain their superior performance, highlighting their substantial investment value.
The study underscores the BAA strategy's potential to improve returns and manage risks, providing a viable asset allocation alternative in volatile market environments. Future research should extend the sample period, diversify assets, and refine risk management models to further validate the strategy's robustness and applicability across different market conditions.

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