ETF资产配置月报（2026年1月）：全球权益看A股，黄金向上趋势延续-20260115

Report Industry Investment Rating No relevant content provided. Core Viewpoints of the Report - The report captures global multi - asset investment opportunities (covering domestic assets such as A - shares, bonds, and gold, as well as overseas equity assets like US stocks, Japanese stocks, and Indian stocks) and designs corresponding allocation schemes according to common investment scenarios. All portfolios can be tracked through corresponding ETF/LOF products [7]. - In January 2026, the allocation suggestions are as follows: A - shares may have short - term momentum but also face callback risks, with a focus on cyclical mid - cap blue - chips led by chemicals, domestic AI, satellites, and semiconductors; the domestic bond market is neutral, and short - term varieties can be focused on; US stocks may maintain a neutral shock pattern; Japanese stocks may have a neutral shock pattern; Indian stocks may have a weak shock pattern; gold may remain strong in the short - term but also face volatility risks, and its medium - to - long - term allocation value is significant [7]. - A two - stage robust multi - asset portfolio design method based on "portfolio insurance + risk budget" is introduced, which is decision - making based on risk characteristics, does not rely on asset return forecasts, and has good robustness while considering both return elasticity and risk control [7]. Summary by Relevant Catalogs 1. Market Review and Allocation Outlook 1.1 Market Review - In 2025, gold performed outstandingly, global equity assets showed differentiation (A - shares, Japanese stocks, and US stocks were strong, while Indian stocks declined slightly), and the bond market was relatively sluggish. The return performance of underlying assets was: gold (58.57%) > CSI 800 (23.91%) > Nikkei 225 (22.26%) > Nasdaq 100 (17.50%) > short - term financing (1.78%) > 7 - 10 - year policy - financial bonds (0.22%) > S&P BSE Sensex ( - 0.40%) [16]. 1.2 Asset Allocation Outlook - A - shares: Economic prosperity and mild inflation recovery support the medium - to - long - term stock market trend, but there are short - term callback risks. Industry themes such as cyclical mid - cap blue - chips led by chemicals, domestic AI, satellites, and semiconductors can be focused on [18]. - Domestic bond market: Due to the risk preference of rising equities and the expectation of mild inflation recovery, bonds are neutral overall, and short - term varieties can be continuously focused on [20]. - US stocks: The US economy still has resilience, but due to the downward revision of interest - rate cut expectations and relatively high valuations, US stocks may maintain a neutral shock pattern in the short - term [22]. - Japanese stocks: Japan's economy is in a benign "wage - price spiral" and is moderately recovering, but with a marginal net outflow of foreign capital, Japanese stocks may have a neutral shock pattern in the short - term [31]. - Indian stocks: The economic prosperity has declined from its peak, and with a marginal net outflow of foreign capital, Indian stocks may have a weak shock pattern in the short - term [34]. - Gold: Geopolitical tensions have pushed gold to new highs. It may remain strong in the short - term but also face volatility risks, and its medium - to - long - term allocation value is significant [38]. 2. Robust Portfolio Design Idea: Two - Stage Method of "Portfolio Insurance + Risk Budget" 2.1 Dilemma of Asset Allocation Models in Domestic Investment Applications - The two classic multi - asset portfolio management methods, mean - variance optimization (MVO) and its derivative models, and risk - budget - based models (such as the risk - parity model), have limitations in domestic investment applications. MVO is highly sensitive to changes in returns and risks, and the risk - parity model may lead to an overly low proportion of equity assets in the portfolio [45]. 2.2 Optimization Idea 1: Using Portfolio Insurance Method to Optimize the Sharpe Ratio of High - Risk Assets - The portfolio insurance strategy can optimize the return - risk ratio of high - volatility assets such as A - shares in the medium - to - long - term. Taking the domestic stock - bond CPPI portfolio as an example, it can achieve better risk performance compared to corresponding portfolios [52]. 2.3 Optimization Idea 2: Integrating Target Allocation Central Risk Budget Strategy - By decomposing the risk budget, the target stock - bond allocation central can be integrated into the risk - budget configuration model, and the allocation weights can be dynamically adjusted according to the changes in asset volatility [59]. 2.4 "Portfolio Insurance + Risk Budget": Balancing Return Elasticity and Risk Control - The two - stage combination design method of "portfolio insurance + risk budget" first uses the CPPI method to optimize the Sharpe ratio of single risk assets and then constructs a risk - budget investment portfolio based on the risk characteristics of each sub - portfolio. It can effectively combine return elasticity and risk control and has good robustness [63]. 3. Stock - Bond Target Allocation Central Risk Budget Portfolio 3.1 Investment Scenarios and Scheme Design - In a low - interest - rate environment, the fixed - income plus strategy can alleviate the problem of declining returns of pure - bond assets. Two strategies are designed: the stock - bond target allocation central risk budget strategy (stock - bond RB) and the "CPPI + RB" two - stage stock - bond target allocation central strategy (stock - bond CPPI_RB), with three types of allocation central combinations of 1:9, 2:8, and 3:7 constructed respectively [67][68][69]. 3.2 Portfolio Performance Analysis - During the back - testing period (January 5, 2015 - December 31, 2025), the performance of the strategy integrating the stock - bond target allocation central risk budget is better than that of the fixed - allocation central stock - bond portfolio, and the two - stage stock - bond CPPI_RB portfolio is better than the stock - bond RB portfolio [70]. 3.3 Allocation Weights and Marginal Changes - The stock - bond allocation of the three types of allocation central portfolios meets the requirements of the target allocation central. At the end of December 2025, the stock - bond RB portfolio moderately increased the weight of A - shares and increased the weight of long - term bonds while reducing the weight of short - term bonds within the bond category [75]. 4. Low - Volatility "Fixed - Income Plus" Portfolio 4.1 Investment Scenarios and Scheme Design - To reduce the volatility risk of the stock - bond portfolio during extreme "stock - bond double - kill" market conditions, an appropriate amount of gold is added. The portfolio is designed using the two - stage method of "portfolio insurance (CPPI) + risk budget (RB)", with a target allocation central of stock:gold:bond = 1:1:4 [80][81]. 4.2 Portfolio Performance Analysis - During the back - testing period (January 1, 2015 - December 31, 2025), the low - volatility "fixed - income plus" strategy has an annualized return of 7.08%, an annualized volatility of 3.47%, a maximum drawdown of - 4.92%, a Sharpe ratio of 1.99, and a Calmar ratio of 1.44 [83]. 4.3 Allocation Weights and Marginal Changes - As of December 31, 2025, the latest weights of the strategy are: CSI 800 (10.78%), gold (5.99%), 7 - 10 - year policy - financial bonds (75.09%), and short - term financing (8.14%). In December 2025, the weight of short - term financing was increased, and the weights of other assets were decreased [90]. 4.4 Strategy Implementation: Tracking Based on ETF Assets - The low - volatility "fixed - income plus" strategy can be well tracked by corresponding ETF assets. As of December 31, 2025, the annualized return of the strategy since 2023 is 9.38%, and the annualized returns of the FOF_of_ETFs portfolio based on ETF net value and on - site price are 9.05% and 9.07% respectively [95]. 5. Global Asset Allocation Portfolio 5.1 Investment Scenarios and Scheme Design - In a volatile global situation, global asset allocation can effectively diversify risks and improve the return - risk ratio of the portfolio. A two - stage FOF portfolio design method of "portfolio insurance (CPPI) + risk parity (RP)" is used [102][104]. 5.2 Global Multi - Asset Allocation Strategy I: A - shares + Bonds + Gold + US Stocks - Performance: During the back - testing period (January 1, 2014 - December 31, 2025), the annualized return is 11.85%, the annualized volatility is 5.94%, the maximum drawdown is - 7.97%, the Sharpe ratio is 1.91, and the Calmar ratio is 1.49. In 2025, it recorded 20.94% [106]. - Allocation Weights and Marginal Changes: As of December 31, 2025, the model allocation weights are: CSI 800 (18.98%), Nasdaq 100 (17.84%), gold (13.66%), and 7 - 10 - year policy - financial bonds (49.51%). In December 2025, the weight of 7 - 10 - year policy - financial bonds was increased, and the weights of other assets were decreased [111]. - Strategy Implementation: The strategy can be well tracked by corresponding ETF/LOF assets. As of December 31, 2025, the annualized return of the strategy since 2023 is 16.92%, and the annualized returns of the FOF_of_ETFs portfolio based on ETF net value and on - site price are 16.53% and 17.04% respectively [119]. 5.3 Global Multi - Asset Allocation Strategy II: A - shares + Bonds + Gold + Cross - Border Equities - Performance: During the back - testing period (January 1, 2014 - December 31, 2025), the annualized return is 10.25%, the annualized volatility is 5.09%, the maximum drawdown is - 9.97%, the Sharpe ratio is 1.94, and the Calmar ratio is 1.03. In 2025, it recorded 13.56% [126]. - Allocation Weights and Marginal Changes: As of December 31, 2025, the model allocation weights are: CSI 800 (9.63%), Nasdaq 100 (9.65%), Nikkei 225 (6.17%), S&P BSE Sensex (17.87%), gold (7.16%), and 7 - 10 - year policy - financial bonds (49.51%). In December 2025, the weights of S&P BSE Sensex and 7 - 10 - year policy - financial bonds were increased, and the weights of other assets were decreased [133]. - Strategy Implementation: The strategy can be well tracked by corresponding ETF/LOF assets. As of December 31, 2025, the annualized return of the strategy since 2023 is 14.06%, and the annualized returns of the FOF_of_ETFs portfolio based on ETF net value and on - site price are 13.60% and 14.06% respectively [145].