1. Report Industry Investment Rating The provided content does not include the industry investment rating. 2. Core View of the Report The report focuses on the localization dilemma of the traditional risk parity model with "low volatility and low returns" in a low - interest - rate environment. By introducing the "Relaxed Risk Parity (RRP)" framework and a dynamic return anchoring mechanism, it constructs an all - weather enhanced strategy that does not rely on macro - timing and balances "risk diversification" and "return elasticity", achieving a logical advancement from localization adaptation to global allocation [1]. 3. Summary According to Relevant Catalogs 3.1 Introduction - In the low - interest - rate era, the traditional single - asset investment framework faces challenges. Asset allocation has become a core source of returns. The mainstream asset - allocation models include the mathematical optimization system and the macro - cycle system, but they face "acclimatization" in the Chinese market. The RRP framework is introduced to solve the problems [15][16][18]. 3.2 Global - scale Main Asset - Allocation Model Introduction - **Logic Divergence and Evolution Path of Mainstream Models**: The mainstream models are divided into the mathematical optimization system starting from the Markowitz mean - variance model and the macro - cycle system represented by the Merrill Lynch Clock. The former evolves from capital allocation to risk allocation, and the latter deepens from state segmentation to timing rotation [20][21][22]. - **China - adaptation Process of Asset - Allocation Models**: The traditional Merrill Lynch Clock has "acclimatization" in the Chinese market. A currency - credit model is proposed as a local alternative. The risk - parity strategy also has a localization dilemma due to the lack of leverage tools and hedging products, and the RRP framework is a solution [26][30]. 3.3 What is Risk Parity? - **Allocation and Hedging, Risk Parity and Factor Parity**: Risk parity is an asset - allocation philosophy based on "risk budgeting". It has evolved into the asset/macro parity mode represented by Bridgewater and the factor parity mode represented by AQR and academia [32]. - **Logical Architecture and Core Calculation Rules**: Based on Euler's theorem, the risk - parity strategy decomposes the total portfolio risk into the risk contributions of each asset and makes them equal through optimization algorithms [33]. 3.4 Relaxed Improvement of Risk Parity - **Logical Reasoning and Core Modeling of RRP**: The traditional risk - parity model has defects such as over - reliance on low - volatility assets and loss of mean - variance efficiency. The RRP framework relaxes the hard constraint of equal risk contributions to a soft - penalty term and constructs a comprehensive optimization model [43][44]. - **Back - test Results**: - **From "Defensive Trap" to "Efficiency Leap"**: Compared with the standard risk - parity portfolio (V1), the relaxed risk - parity portfolio (V2) has significantly improved in terms of annualized return, Sharpe ratio, winning rate, and has more flexible bond - leverage use and dynamic portfolio structure [70]. - **From "Local Trial - and - Error" to "Global Allocation"**: The globalized relaxed risk - parity portfolio (V3) has a diversified structure and lower trading friction. It can use the dislocation of Sino - US economic cycles to achieve better performance [76][79]. - **Generalization Ability of the Model under Different Parameter Windows**: When the parameter - estimation window is extended from 1 year to 2 years, the RRP model still shows better risk - return characteristics, proving its long - term effectiveness [85]. 3.5 Subsequent Strategy Optimization - **AI - enabled**: Introduce a deep - reinforcement learning framework to construct an intelligent agent that can dynamically adjust core parameters according to the macro - environment [86]. - **Response to Extreme Environments**: Use the idea of volatility parity and graph - theory algorithms to improve the robustness of the strategy in extreme environments [88]. - **Paradigm Reconstruction**: Shift from asset - based to factor - based risk control, and construct a three - dimensional allocation system [89].

Group 1 - The report discusses the re-evaluation of the All-Weather Strategy, emphasizing the need for a more balanced asset allocation approach in the context of China's low bond volatility, which leads to higher bond allocations than intended under traditional risk parity models [3][20]. - The concept of "Scenario Parity" is introduced, where asset allocation is based on different macroeconomic scenarios (growth and inflation), allowing for a more tailored asset basket that can enhance returns compared to traditional risk parity [3][21]. - The report highlights the performance of the All-Weather ETF launched by Bridgewater, which has shown resilience and recovery from market volatility, with a maximum drawdown of 8.78% shortly after its launch [8][12]. Group 2 - The report outlines the construction of a "Scenario Parity" portfolio using regression analysis to measure asset exposure to macroeconomic factors, resulting in a more effective asset allocation strategy that improves returns while reducing bond exposure [3][22]. - The performance metrics of various asset allocation strategies are compared, showing that the "Scenario Parity" approach yields higher annualized returns and lower drawdowns compared to traditional risk parity strategies [29][55]. - The report emphasizes the importance of macro sensitivity in constructing portfolios, demonstrating that portfolios based on sensitivity measures outperform those based solely on regression analysis, particularly in volatile market conditions [34][55]. Group 3 - The report explores the application of the All-Weather strategy within equity assets, indicating that a focus on macro exposure can lead to better risk diversification and performance, especially in uncertain market environments [41][43]. - The analysis of industry ETFs reveals significant differences in macro exposure, suggesting that a more nuanced approach to sector allocation can enhance overall portfolio performance [45][48]. - The report concludes that using macro sensitivity to guide asset selection within equity portfolios can lead to improved risk-adjusted returns, highlighting the effectiveness of this strategy in various economic scenarios [55][56].