中银量化大类资产跟踪 A 股市场缩量反弹，贵金属涨幅居前 金融工程| 证券研究报告 —周报 2025 年 11 月 30 日 股票市场概览 本周 A 股市场整体上涨，港股市场整体上涨，美股市场普遍上涨，其 他海外权益市场普遍上涨。 A 股风格与拥挤度 成长 vs 红利：相对拥挤度及超额净值近期处于历史较高位置，需注 意成长风格的配置风险。 小盘 vs 大盘：相对拥挤度及超额净值均未处于历史高位，小盘风格 当前具有较高的配置性价比。 微盘股 vs 中证 800：相对拥挤度及超额净值持续处于历史高位，需注 意微盘股风格的配置风险。 A 股行情跟踪 A 股估值与股债性价比 A 股资金面 汇率市场 近一周在岸人民币较美元升值，离岸人民币较美元升值。 商品市场 本周中国商品市场整体上涨，美国商品市场整体下跌。 风险提示 量化模型因市场剧烈变动失效。 中银国际证券股份有限公司 具备证券投资咨询业务资格 金融工程 证券分析师: 郭策 (8610) 66229081 ce.guo@bocichina.com 证券投资咨询业务证书编号：S1300522080002 联系人：宋坤笛 (8610) 83949524 kundi.s ...

Group 1: US Economic Outlook - The US economy is experiencing short-term "stagflation," with GDP growth expected to slow from 2.8% in 2024 to 1.7% in 2025, and inflation pressures may rebound, with PCE inflation projected to rise to 2.8% in Q3 and 2.9% in Q4 of 2025 [2][24] - The real estate market continues to show signs of stagnation, with high interest rates leading to historically low purchasing power and sales, while many homeowners are reluctant to move due to locked-in low mortgage rates, resulting in tight inventory [2][29] - Corporate earnings growth has been downgraded, particularly in industries sensitive to trade wars and economic cycles, such as industrials, energy, and materials [3] Group 2: Federal Reserve and Monetary Policy - The Federal Reserve is expected to cut interest rates twice between September and December 2025, with a potential further two cuts in 2026, bringing the policy rate down to a range of 3.25%-3.5% [4] - However, due to potential increased influence from the White House on the Federal Reserve, market inflation expectations remain unstable, and rising government debt may keep Treasury yields elevated [5] Group 3: Investment Recommendations - Short-term investment focus should be on sectors such as healthcare, consumer staples, communication services, materials, and industrials [7] - Overall, the US stock market is in the late stages of a bull market, suitable for long-term dollar-cost averaging, with asset allocation recommendations to overweight commodities, standard allocation to stocks and cash, and underweight bonds, while being bearish on the US dollar and bullish on the euro, pound, and emerging market currencies [8] Group 4: China Economic Outlook - China's economy is entering a phase of weak recovery, with Q1 2025 GDP growth peaking at 5.4% but expected to decline to 4.7% in Q4 due to base effects and diminishing policy impacts [9] - The real estate market is stabilizing, with a recovery in second-hand home sales in first-tier cities and gradual inventory digestion, leading to expectations of price stabilization in the second half of 2025 [10] - Deflationary pressures are bottoming out, and corporate profits are expected to rebound, supported by a continuation of accommodative policies, including a potential 10 basis point rate cut in Q4 2025 [11][12] Group 5: Currency and Asset Allocation - The Chinese yuan is expected to appreciate moderately, potentially reaching 7.1 by the end of 2025 and 7.05 by the end of 2026 [15] - Asset allocation recommendations for China include overweighting stocks, standard allocation to commodities and bonds, and underweighting cash [16] - The stock market is entering the second phase of a bull market, with accelerated sector rotation, and short-term optimism is noted for AI hardware and applications, internet, healthcare, chemicals, machinery, and consumer staples [17]

Quantitative Models and Construction Methods 1. Model Name: Black-Litterman (BL) Model - **Model Construction Idea**: The BL model is an improvement over the traditional mean-variance optimization (MVO) model. It integrates subjective views with quantitative models using Bayesian theory to optimize asset allocation weights. This approach addresses the sensitivity of MVO to expected returns and provides a more robust asset allocation solution[12][13]. - **Model Construction Process**: - The BL model combines subjective views of investors with market equilibrium returns to derive optimized portfolio weights. - The model uses the following formula to calculate the posterior expected returns: $ \mu = [( \tau \Sigma )^{-1} + P^T \Omega^{-1} P]^{-1} [( \tau \Sigma )^{-1} \Pi + P^T \Omega^{-1} Q] $ - $\mu$: Posterior expected returns - $\tau$: Scalar representing the uncertainty in the prior estimate of returns - $\Sigma$: Covariance matrix of asset returns - $\Pi$: Equilibrium returns derived from market capitalization weights - $P$: Matrix representing the views on assets - $\Omega$: Covariance matrix of the views - $Q$: Vector of expected returns based on the views - The optimized portfolio weights are then derived using the posterior expected returns and the covariance matrix[12][13]. - **Model Evaluation**: The BL model effectively addresses the sensitivity of MVO to expected returns and provides a more robust and efficient asset allocation framework. It also allows for the incorporation of subjective views, making it more flexible and practical for real-world applications[12]. 2. Model Name: Risk Parity Model - **Model Construction Idea**: The risk parity model aims to equalize the risk contribution of each asset in a portfolio. It is an improvement over the traditional mean-variance optimization model and focuses on diversifying risk rather than capital allocation[17][18]. - **Model Construction Process**: - Step 1: Select appropriate underlying assets. - Step 2: Calculate the risk contribution of each asset to the portfolio using the formula: $ RC_i = w_i \cdot \sigma_i \cdot \rho_{i,portfolio} $ - $RC_i$: Risk contribution of asset $i$ - $w_i$: Weight of asset $i$ - $\sigma_i$: Volatility of asset $i$ - $\rho_{i,portfolio}$: Correlation of asset $i$ with the portfolio - Step 3: Solve the optimization problem to minimize the deviation between actual and target risk contributions, subject to the constraint that the sum of weights equals 1[18][19]. - **Model Evaluation**: The risk parity model provides a balanced risk allocation across assets, making it suitable for achieving stable returns across different economic cycles. It is particularly effective in reducing portfolio volatility and drawdowns[18]. 3. Model Name: Macro Factor-Based Asset Allocation Model - **Model Construction Idea**: This model constructs a macro factor system covering six key risks: growth, inflation, interest rates, credit, exchange rates, and liquidity. It bridges macroeconomic research with asset allocation by translating macroeconomic views into actionable portfolio strategies[21][22]. - **Model Construction Process**: - Step 1: Calculate the factor exposure levels of assets at the end of each month. - Step 2: Use a risk parity portfolio as the benchmark and calculate the benchmark factor exposure. - Step 3: Based on macroeconomic forecasts for the next month, assign subjective factor deviation values. For example, if inflation is expected to rise, assign a positive deviation to the inflation factor. - Step 4: Combine the benchmark factor exposure with the subjective factor deviations to derive the target factor exposure for the portfolio. - Step 5: Solve the optimization problem to determine the asset allocation weights for the next month[22][25]. - **Model Evaluation**: This model effectively incorporates macroeconomic views into asset allocation, providing a systematic framework for translating macroeconomic insights into portfolio decisions. It is particularly useful for capturing macroeconomic trends and their impact on asset performance[21]. --- Model Backtesting Results 1. Black-Litterman (BL) Model - **Domestic Asset BL Model 1**: Weekly return: -0.32%, November return: 0.05%, 2025 YTD return: 4.0%, annualized volatility: 2.18%, maximum drawdown: 1.31%[14][16][17] - **Domestic Asset BL Model 2**: Weekly return: -0.15%, November return: 0.08%, 2025 YTD return: 3.77%, annualized volatility: 1.95%, maximum drawdown: 1.06%[14][16][17] - **Global Asset BL Model 1**: Weekly return: -0.17%, November return: -0.26%, 2025 YTD return: 0.78%, annualized volatility: 2.0%, maximum drawdown: 1.64%[14][16][17] - **Global Asset BL Model 2**: Weekly return: 0.01%, November return: 0.08%, 2025 YTD return: 2.7%, annualized volatility: 1.59%, maximum drawdown: 1.28%[14][16][17] 2. Risk Parity Model - **Domestic Asset Risk Parity Model**: Weekly return: -0.27%, November return: -0.09%, 2025 YTD return: 3.6%, annualized volatility: 1.32%, maximum drawdown: 0.76%[20][28] - **Global Asset Risk Parity Model**: Weekly return: -0.2%, November return: -0.07%, 2025 YTD return: 3.04%, annualized volatility: 1.42%, maximum drawdown: 1.2%[20][28] 3. Macro Factor-Based Asset Allocation Model - **Macro Factor-Based Asset Allocation Model**: Weekly return: -0.31%, November return: -0.01%, 2025 YTD return: 4.43%, annualized volatility: 1.55%, maximum drawdown: 0.64%[27][28]

Core Viewpoint - The convertible bond market shows signs of resilience with a notable increase in the convertible bond ETF and active trading, despite underlying economic uncertainties and market volatility [2][3]. Group 1: Market Performance - As of November 28, 2025, the CSI Convertible Bond and Exchangeable Bond Index rose by 0.42%, while the convertible bond ETF increased by 0.49%, reaching a price of 13.36 yuan [2]. - Over the past six months, the convertible bond ETF has accumulated a rise of 11.37% [2]. - The trading volume for the convertible bond ETF was active, with a turnover rate of 10.08% and a transaction value of 5.712 billion yuan [2]. Group 2: Monetary Policy and Liquidity - The central bank conducted a reverse repurchase operation of 356.4 billion yuan at a fixed rate of 1.40% on November 27, resulting in a net injection of 56.4 billion yuan after accounting for maturing reverse repos [2]. Group 3: REITs Market Outlook - According to Huatai Fixed Income, the REITs market is expected to have limited trend opportunities in 2026, with a more pronounced differentiation in fundamentals [2]. - The investment strategy should focus on selecting high-quality assets with stable fundamentals and reasonable valuations, as REITs will play a more significant role in diversified asset allocation in a low-interest-rate environment [2]. Group 4: Convertible Bond ETF Insights - The latest size of the convertible bond ETF reached 56.8 billion yuan, with a recent net outflow of 5.3472 million yuan [3]. - Over the past five trading days, the ETF has attracted a total of 38.637 million yuan [3]. - The convertible bond ETF closely tracks the CSI Convertible Bond and Exchangeable Bond Index, which is composed of convertible and exchangeable bonds listed on the Shanghai and Shenzhen stock exchanges [3].

Group 1 - The theme of the CITIC Futures 2026 Annual Strategy Conference is "Sailing Forward Amidst Waves," focusing on global economic changes, macro policy orientation, and asset allocation [1] - CITIC Futures Chairman Dou Changhong highlighted the dual challenges of restructuring global order and trade rules while also embracing a new wave of technological revolution and green transformation [1] - The conference emphasized the importance of seizing historical opportunities during the transitional phase of the economy, particularly as China enters the 14th Five-Year Plan [1] Group 2 - CITIC Securities' Chief Macro Analyst Cui Rong and his team predict a temporary period of clarity in the global macro environment for 2026, with reduced uncertainties in geopolitics, fiscal, and monetary policies [2] - They expect a moderate acceleration in economic growth in the US, Europe, and Japan, alongside a return of inflation concerns to a "comfortable zone" [2] - The anticipated global interest rate cuts in 2026 are expected to be less pronounced than in 2025, with a stronger US dollar in the first half of the year, leading to lower liquidity in global financial markets [2] Group 3 - CITIC Futures Research Institute Deputy Director Zeng Ning maintains an optimistic macro outlook for 2026, with a continued easing of global liquidity driven by the Federal Reserve's rate-cutting cycle [2] - The asset allocation strategy for 2026 suggests a balanced approach, with an increased weight on commodities while being mindful of internal differentiation [2] - Precious metals are expected to remain a strong hedge against sovereign credit currency depreciation, while supply-constrained and demand-growing non-ferrous metals are also favored [3] Group 4 - The outlook for black construction materials indicates a stable demand-supply dynamic, with potential for long positions at relative valuation bottoms once global recovery becomes clearer [3] - Oil is projected to face significant inventory accumulation in 2026, with expectations of downward pressure on price levels, suggesting a cautious approach to long positions until supply dynamics stabilize [3]

Core Viewpoint - The commodity ETF market has experienced significant growth in both scale and performance, indicating its transition from a niche option to a core strategic asset in asset allocation [3][4]. Group 1: Growth in Scale and Performance - The total scale of commodity ETFs has increased by over 200% since the beginning of the year, with a total net inflow of 966.2 billion yuan, bringing the total scale to 2,267 billion yuan [5][7]. - Gold ETFs have emerged as the main driver of this growth, with an average scale increase of 4.8 times this year, significantly outperforming traditional equity and bond assets [7][9]. Group 2: Factors Driving Growth - The explosive growth of commodity ETFs is attributed to a combination of macroeconomic conditions, market structure, and investor awareness, with gold ETFs particularly benefiting from their inflation-hedging and asset preservation functions [9][10]. - The price of gold has surged, reaching a peak of over 4,100 USD per ounce, which has been a key factor in the strong performance of gold ETFs, with returns close to 50% this year [9][21]. Group 3: Investment Value Analysis - Gold ETFs dominate the commodity ETF market, accounting for over 95% of the total scale, making it essential to analyze future gold price trends for assessing the investment value of commodity ETFs [17][18]. - The anticipated easing of monetary policy by the Federal Reserve is expected to support gold prices, as historical trends show that a rate-cutting cycle typically leads to a weaker dollar and stronger gold prices [18][19]. Group 4: Selection and Allocation Strategies - For investors focused on asset preservation and risk hedging, gold ETFs are the preferred choice, while those looking to capitalize on economic cycles may consider allocating to industrial metal or energy ETFs [24][25]. - A diversified allocation strategy is suggested, with varying proportions of gold ETFs, industrial metal ETFs, and energy ETFs based on the investor's risk tolerance and market outlook [25]. Group 5: Future Outlook - The future of the commodity ETF market appears promising, with ongoing product innovation expected to solidify commodity ETFs as a standard allocation in investment portfolios, especially in times of global uncertainty [26].

中证报中证网讯（记者 葛瑶 王超）11月26日，中信期货2026年度策略会在上海浦东召开。本次策略会 以"破浪前行，扬帆起航"为主题，共设置1个主论坛及8个分论坛，以多元化视角对2025年下半年以来的 宏观、权益、债券、大宗商品、汇率、海外市场等议题进行深入探讨，并对2026年相关议题做出展望。 窦长宏介绍，2025年中信期货保证金规模突破2000亿元，并创下新高，成交、持仓、交割规模均同比增 长。公司不断做深做实产业服务，服务产业客户超过1万家，实现套保金额近8000亿元；持续推出贴合 产业链风险管理诉求的衍生产品结构和期现结合产品，风险子公司服务实体企业2000余家，其中大部分 为中小微企业，服务实体交易金额超1500亿元。国际化方面，引进来和走出去业务规模均创历史新高， 全球市场的交易结算承做能力持续增强。 中国宏观经济学会副会长祝宝良发表了关于《2026年我国宏观经济形势和政策取向》的主题演讲。他认 为，2026年，要坚持稳中求进工作总基调，实施更加积极有为的财政政策和适度宽松的货币政策，不断 深化改革、扩大开放，着力扩大内需，着力增强微观主体活力，着力稳定市场主体信心，推动经济稳中 向好。 中信期货 ...

大类资产早报 研究中心宏观团队 2025/11/25 | 全 球 资 产 市 场 表 现 | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 主要经济体10年期国债 | | | | | | | | | | 美国 | | 英国 | 法国 | 德国 | 意大利 | 西班牙 | 瑞士 | 希腊 | | 最新 | 4.026 | 4.537 | 3.446 | 2.691 | 3.439 | 3.194 | 0.145 | 3.302 | | 日本 | | 巴西 | 中国 | 韩国 | 澳大利亚 | 新西兰 | | | | 最新 | 1.773 | 6.185 | 1.813 | - | 4.443 | 4.162 | | | | 主要经济体2年期国债 | | | | | | | | | | 美国 | | 英国 | 德国 | 日本 | 意大利 | 中国（1Y收益 率） | 韩国 | 澳大利亚 | | 最新 | 3.498 | 3.778 | 2.009 | 0.941 | 2.188 | 1.404 | - | 3.6 ...

Core Viewpoint - The article discusses the investment philosophies of various individuals, particularly focusing on the insights shared by Duan Yongping, highlighting the subjective nature of investment strategies and the importance of aligning them with personal circumstances [1][3][6]. Group 1: Investment Strategies - Duan Yongping emphasizes the importance of investing in companies with a competitive moat, such as Apple, Moutai, and Tencent, but does not provide specific criteria for identifying such companies [1][3]. - The article mentions various successful investment strategies from different individuals, including quantitative rotation, value investing, and asset allocation, suggesting that there are multiple paths to success in the capital markets [2][3]. - It is noted that Duan's investment approach may not be suitable for everyone, particularly for those without the same level of financial security or understanding of market dynamics [3][4]. Group 2: Personalization of Investment - The article stresses that each investor must find a strategy that matches their own conditions, as not everyone can adopt the same methods successfully [3][7]. - It highlights the importance of personal experience and understanding in investment, suggesting that what works for one individual may not work for another [6][7]. - The discussion includes the notion that investment is a highly personalized endeavor, and individuals should absorb wisdom from various sources to refine their own investment frameworks [7][8]. Group 3: Market Insights - The article reflects on the current market environment, indicating that while broad investment principles may hold true, the application of these principles can vary significantly based on market conditions [5][9]. - It mentions the potential for significant returns in the stock market, but also acknowledges the challenges and risks involved in identifying future successful companies [5][11]. - The discussion includes references to the financial performance of companies like OPPO and VIVO, suggesting that strong cash flow from these businesses can support investment strategies [9][10].

Economic Outlook - The global economic growth is expected to slow to 3.1% in 2026, down 2 percentage points from 2024, but remains resilient[2] - Developed economies are projected to grow at 1.6%, with the U.S. experiencing a slowdown and the Eurozone showing weak momentum[2] Interest Rates and Market Sensitivity - The U.S. policy interest rate is anticipated to decline to a range of 3.0%–3.25%, while the Eurozone will maintain around 2.15%[2] - High interest rates combined with high debt levels have intensified the interaction between fiscal and monetary policies, leading to quicker market responses to policy signals[2] Asset Correlation and Investment Strategy - There is an increasing correlation between risk and non-risk assets, with traditional linear assumptions becoming less applicable[2][3] - The shift from asset diversification to path diversification is necessary to enhance portfolio resilience in a chaotic market environment[7][8] Market Dynamics - The relationship between assets is more prone to convergence under disturbances, with reduced inverse relationships between stocks and bonds[7] - Price formation is increasingly influenced by policy changes and market narratives, necessitating a focus on potential price trajectories rather than merely expanding asset classes[8] Future Asset Performance - U.S. long-term yields are expected to fluctuate within a range of 3.9%–4.2%[10] - Emerging markets, particularly India and parts of Latin America, are likely to perform better than developed markets due to structural adjustments and valuation recoveries[10] Gold and Currency Outlook - Gold is expected to maintain a strong position supported by central bank reserve demands and policy uncertainties[10] - The U.S. dollar is projected to remain weak, with the index likely trading between 95 and 100, favoring non-U.S. currencies[10]