- The Black-Litterman (BL) model is an improved version of the mean-variance optimization (MVO) model developed by Fisher Black and Robert Litterman in 1990. It combines Bayesian theory with quantitative asset allocation models, allowing investors to incorporate subjective views into asset return forecasts and optimize portfolio weights. This model addresses MVO's sensitivity to expected returns and provides a more robust framework for efficient asset allocation[12][13][14] - The BL model was implemented for both global and domestic assets. For global assets, it utilized indices such as the S&P 500, Hang Seng Index, and COMEX Gold. For domestic assets, it included indices like CSI 300, CSI 1000, and SHFE Gold. Two variations of the BL model were constructed for each asset category[13][14][18] - The Risk Parity model, introduced by Bridgewater in 2005, aims to equalize risk contributions across asset classes in a portfolio. It calculates initial asset weights based on expected volatility and correlation, then optimizes deviations between actual and expected risk contributions to determine final portfolio weights[17][18][20] - The Risk Parity model was applied to both global and domestic assets. Global assets included indices such as CSI 300, S&P 500, and COMEX Gold, while domestic assets incorporated CSI 300, CSI 1000, and SHFE Gold. The model followed a three-step process: selecting assets, calculating risk contributions, and solving optimization problems for portfolio weights[18][20][21] - The Macro Factor-based Asset Allocation model constructs a framework using six macroeconomic risk factors: growth, inflation, interest rates, credit, exchange rates, and liquidity. It employs Factor Mimicking Portfolio methods to calculate high-frequency macro factors and integrates subjective views on macroeconomic conditions into asset allocation decisions[22][24][25] - The Macro Factor-based model involves four steps: calculating factor exposures for assets, determining benchmark factor exposures using a Risk Parity portfolio, incorporating subjective factor deviations based on macroeconomic forecasts, and solving for asset weights that align with target factor exposures[22][24][25] Model Performance Metrics - Domestic BL Model 1: Weekly return -0.11%, September return -0.14%, 2025 YTD return 3.23%, annualized volatility 2.19%, maximum drawdown 1.31%[14][17] - Domestic BL Model 2: Weekly return -0.11%, September return -0.13%, 2025 YTD return 2.84%, annualized volatility 1.99%, maximum drawdown 1.06%[14][17] - Global BL Model 1: Weekly return 0.04%, September return 0.11%, 2025 YTD return 0.84%, annualized volatility 1.99%, maximum drawdown 1.64%[14][17] - Global BL Model 2: Weekly return 0.00%, September return 0.03%, 2025 YTD return 1.84%, annualized volatility 1.63%, maximum drawdown 1.28%[14][17] - Domestic Risk Parity Model: Weekly return -0.06%, September return 0.05%, 2025 YTD return 2.99%, annualized volatility 1.35%, maximum drawdown 0.76%[20][21] - Global Risk Parity Model: Weekly return -0.07%, September return 0.13%, 2025 YTD return 2.50%, annualized volatility 1.48%, maximum drawdown 1.20%[20][21] - Macro Factor-based Model: Weekly return 0.04%, September return 0.26%, 2025 YTD return 3.29%, annualized volatility 1.32%, maximum drawdown 0.64%[26][27]

Report Overview - The report is a weekly update on public offering funds, specifically focusing on ETF strategy index tracking as of September 29, 2025 [1] Investment Ratings - No industry investment ratings are provided in the report Core Views - The report presents several ETF strategy indices constructed with the help of ETFs, aiming to convert quantitative models or subjective views into practical investment strategies. The performance and positions of these indices are tracked on a weekly basis [12] Summary by Index 1. ETF Strategy Index Tracking - **Overall Performance Last Week**: - The Huabao Research Size Rotation ETF Strategy Index had a weekly return of 1.09%, outperforming the CSI 800 by 0.05% [13] - The Huabao Research Quantitative Firewheel ETF Strategy Index had a weekly return of 2.24%, outperforming the CSI 800 by 1.19% [13] - The Huabao Research Quantitative Balance ETF Strategy Index had a weekly return of 0.40%, underperforming the SSE 50 by 0.67% [13] - The Huabao Research SmartBeta Enhanced ETF Strategy Index had a weekly return of 1.03%, underperforming the CSI 800 by -0.02% [13] - The Huabao Research Hot - Spot Tracking ETF Strategy Index had a weekly return of -0.09%, underperforming the CSI All - Share by -0.29% [13] - The Huabao Research Bond ETF Duration Strategy Index had a weekly return of -0.02%, outperforming the ChinaBond Aggregate Index by 0.23% [13] 1.1 Huabao Research Size Rotation ETF Strategy Index - **Strategy**: Utilizes multi - dimensional technical indicators and a machine - learning model to predict the return difference between the Shenwan Large - Cap Index and the Shenwan Small - Cap Index. It outputs weekly signals to determine positions [14] - **Performance**: As of September 26, 2025, the excess return since 2024 was 18.78%, the excess return in the past month was -0.34%, and the excess return in the past week was 0.05% [14] - **Position**: As of September 26, 2025, it held 100% of the SSE 50 ETF [19] 1.2 Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: Uses price - volume indicators to time self - built Barra factors and maps timing signals to ETFs based on their exposure to 9 major Barra factors [19] - **Performance**: As of September 26, 2025, the excess return since 2024 was 17.37%, the excess return in the past month was 0.49%, and the excess return in the past week was -0.02% [19] - **Position**: As of September 26, 2025, it held multiple ETFs, including the ChiNext Growth ETF (9.77%), CSI 2000 ETF (25.25%), STAR 50 ETF (23.15%), etc. [23] 1.3 Huabao Research Quantitative Firewheel ETF Strategy Index - **Strategy**: Adopts a multi - factor approach, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behavior. It uses valuation and crowding signals to identify industry risks [23] - **Performance**: As of September 26, 2025, the excess return since 2024 was 26.78%, the excess return in the past month was 6.01%, and the excess return in the past week was 1.19% [23] - **Position**: As of September 26, 2025, it held the New Energy ETF (21.61%), Electronics ETF (20.86%), Communication ETF (19.96%), etc. [27] 1.4 Huabao Research Quantitative Balance ETF Strategy Index - **Strategy**: Employs a multi - factor system covering economic fundamentals, liquidity, technical aspects, and investor behavior to construct a quantitative timing system for equity market trend analysis and size - style prediction [27] - **Performance**: As of September 26, 2025, the excess return since 2024 was -10.28%, the excess return in the past month was -0.99%, and the excess return in the past week was -0.67% [27] - **Position**: As of September 26, 2025, it held the 10 - Year Treasury Bond ETF (9.28%), CSI 500 Enhanced ETF (6.14%), etc. [32] 1.5 Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: Tracks market sentiment, industry events, investor sentiment, professional opinions, policy changes, and historical trends to construct an ETF portfolio that captures market hot - spots [33] - **Performance**: As of September 26, 2025, the excess return in the past month was 1.15%, and the excess return in the past week was -0.29% [33] - **Position**: As of September 26, 2025, it held the Color Metals 50 ETF (33.02%), Hong Kong Stock Connect Medical ETF (24.12%), etc. [37] 1.6 Huabao Research Bond ETF Duration Strategy Index - **Strategy**: Uses bond market liquidity and price - volume indicators to select effective timing factors and predicts bond yields through machine learning. It adjusts long - duration positions based on expected yields [37] - **Performance**: As of September 26, 2025, the excess return in the past month was 0.53%, and the excess return in the past week was 0.23%. Since 2024, the excess return was 5.59%, and since its establishment, it was 8.80% [40] - **Position**: As of September 26, 2025, it held the Short - Term Financing ETF (50.03%), 10 - Year Treasury Bond ETF (24.99%), etc. [41]

Group 1 - The report indicates that the overall asset allocation strategy has experienced fluctuations due to domestic equity asset volatility, with various models recording different degrees of decline [1][4][7] - The performance of major asset classes from September 15 to September 19, 2025, shows that the S&P 500, Hang Seng Index, and other indices recorded gains, while convertible bonds and gold experienced declines [7][10] - The domestic asset BL model 1 and model 2 both reported a weekly return of -0.04%, while the global asset BL models had slightly better performance with a return of -0.01% for model 1 and -0.03% for model 2 [15][17] Group 2 - The Black-Litterman (BL) model is highlighted as an improvement over traditional mean-variance models, integrating subjective views with quantitative models to optimize asset allocation [12][13] - The domestic asset risk parity model achieved a return of -0.02% for the week, while the global asset risk parity model recorded a positive return of 0.05% [21][22] - The macro factor-based asset allocation strategy reported a weekly return of -0.1%, with a year-to-date return of 3.25%, indicating its performance amidst changing economic conditions [27][28]

谁都不会想到，那个无数人用来种草护肤品、寻找旅游攻略的小红书，竟会埋藏着一桩惊天金融案的导火索。 2023年的某一天，时年34岁的清华学霸吴舰，在平台上发布了一篇看似普通的炫耀帖——"不敢发朋友圈，自己心 态还是太年轻，想找个没人认识的地方偷偷炫耀下……" 轻描淡写的几句话背后，是一张令人瞠目结舌的薪酬截图：2350万美元，折合人民币约1.67亿元。 这个数字是什么概念？ 甚至相当于顶级对冲基金高管年薪的数倍，或超过了知名投资银行CEO的薪酬水平。 相比吴舰往年的收入水平，2022年的这笔报酬出现了难以解释的倍数级增长。在量化投资这个讲究平稳回报的行 业，这样的薪酬波动就是一个巨大的警报。 很快，这篇帖子在量化金融圈内流传。 业内人士的疑惑与质疑声渐起。 它相当于一个普通北上广深白领工作上千年的总收入；足以买下一整栋豪华公寓楼；甚至超过了某些上市公司一 整年的净利润。 即便在遍地富豪的华尔街，这也是一个令人侧目的数字。 一个年仅34岁的量化研究员，即便再优秀，何以能获得如此惊人的报酬？ 是做出了革命性的模型突破？还是管理了异常成功的基金产品？ 抑或是……另有隐情？ 这些疑问后来终是传到了Two Sigma高管 ...

以下文章来源于风云君的研究笔记 ，作者专注私募研究的 风云君的研究笔记 . 深耕私募行业多年，专注私募基金各个策略以及资产配置，希望能分享给大家更深入、更专业的私募那 些事。 过去几年，桥水全天候策略产品表现非常出色，最差产品线一年收益率也在10%到14%之间，平 均收益率大约在16%左右，真正实现了跨越牛熊周期的长期收益。 当然，其策略本身的赚钱逻辑也被越来越多投资人接受。 风险提示：本文所提到的观点仅代表个人的意见，所涉及标的不作推荐，据此买卖，风险自负。 作者： 风云君的研究笔记 来源：雪球 节目预告：本周三晚，风云君会邀请雪球基金投研举办一场"宏观策略"的专场直播，从市场环境到策略 深度解读。点击添加风云君企微提前报名>> 上周，上证指数一度逼近3900点整数关口，A股情绪很是火热。 但比大盘更"火热"的，是桥水旗下的全天候策略产品。 到底"火热"到什么程度？ 据了解，早在8月份，产品上架即售罄。还因为认购过于火爆，某头部券商直接开启白名单制，大 部分只对高净客户开放，另外各种配售机制也大幅抬高了申购门槛。很多投资者直呼"买不起"， 只能望而却步。 桥水全天候被市场"疯抢" 自然 离不开其策略的优秀 ...

Group 1: Core Insights - The report suggests an overweight allocation to small-cap stocks for September, based on a quantitative model signal of 0.17 at the end of August, indicating a preference for small-cap style [1] - The long-term view remains optimistic for small-cap stocks, with the current market capitalization factor valuation spread at 1.01, which is still below the historical peak range of 1.7 to 2.6 [1] - Year-to-date, the small-cap rotation strategy has yielded a return of 28.19%, with an excess return of 4.24% compared to benchmarks like CSI 300 and CSI 2000 [1] Group 2: Value and Growth Style Rotation - The monthly quantitative model signal for value and growth style is 0, suggesting an equal-weight allocation for September [1] - The year-to-date return for the value and growth style rotation strategy is 14.33%, with an excess return of 1.35% relative to equal-weight benchmarks [1] Group 3: Factor Performance Tracking - Among eight major factors, volatility and large-cap factors showed positive returns in August, while liquidity and quality factors had negative returns [2] - Year-to-date, volatility and momentum factors have performed positively, whereas liquidity and large-cap factors have shown negative returns [2] - In August, beta, large-cap, and short-term reversal factors had positive returns, while profitability quality, seasonality, and liquidity factors had negative returns [2] Group 4: Factor Covariance Matrix Update - The report updates the stock covariance matrix, which is crucial for predicting portfolio risk, using a multi-factor model to combine factor covariance and stock-specific risk matrices [2]

引子 摩根士丹利那帮西装革履的家伙又在放风了，说美联储要玩把大的，降息幅度可能超预期。消息一出，华尔街那帮老 狐狸立刻开始倒腾美债，曲线陡峭化交易玩得飞起。可咱们A股呢？我盯着屏幕直乐——每次这种全球级别的资金流 动，最后受伤的总是散户。 这不，最近行情刚有点起色，身边几个老哥就开始摩拳擦掌。老张说要"持股待涨"，老王嚷嚷着"强者恒强"，最绝的是 老李，天天盯着超跌股准备抄底。我看着他们热血沸腾的样子，突然想起十八年前那个被牛市收割的自己。 一、降息狂欢下的冷思考 摩根士丹利那份报告我翻来覆去看了三遍。他们给美联储设计了三个剧本：财政刺激（10%概率）、通胀容忍（10%概 率）、经济衰退（30%概率）。最逗的是那个叫Matthew Hornbach的分析师，一边建议做多5年期美债，一边又让客户 买2026年期货——这操作跟咱们散户追涨杀跌有啥区别？ 但问题在于，当这些华尔街精英们在玩利率曲线游戏时，咱们普通投资者在干嘛？我见过太多人一听说降息就冲进股 市，结果踩进牛市陷阱里爬都爬不出来。就像上周三，券商板块突然暴动，群里立刻炸锅："牛市旗手动了！""这次肯 定要突破！"结果呢？第二天直接闷杀。 二、牛市四大致 ...

Group 1 - The core viewpoint of the articles is that the A-share market is experiencing a gradual recovery in sentiment, with structural opportunities emerging, particularly in mid-cap growth stocks that were previously undervalued [1][2] - The market is entering a critical window for style rebalancing, with a shift in risk appetite towards rational equilibrium, leading to potential investment opportunities in quality mid-cap growth stocks driven by valuation recovery and performance improvement [1][2] - The launch of the CITIC Prudential CSI A500 Index Enhanced Securities Investment Fund aims to capture excess returns through quantitative models amid changing market styles [1][2] Group 2 - The CITIC Prudential CSI A500 Index is seen as having high cost-effectiveness for allocation, with a significant overlap with the CSI 300 Index and inclusion of high-growth sectors like semiconductor equipment and industrial robots [2] - The index reflects the performance of 500 representative listed companies across various industries, aiming to depict the overall performance of core assets amid China's economic transformation [2] - The investment strategy focuses on both fundamental analysis and quantitative factors, with a particular emphasis on identifying mispriced opportunities in mid-cap stocks [3][5] Group 3 - The quantitative enhancement strategy is divided into two approaches: one focusing on fundamental alpha factors for stocks overlapping with the CSI 300 Index, and the other leveraging quantitative factors to identify mispriced mid-cap stocks [3][5] - The team has shifted from static risk analysis to a more dynamic risk management approach, allowing for customized risk thresholds based on various factors such as sentiment and liquidity [5][6] - Continuous iteration and adaptation of quantitative strategies are emphasized, particularly in response to changing market conditions and the effectiveness of different factors [4][5]

Core Viewpoint - Zhongyuan Trust celebrates its 40th anniversary, highlighting its evolution from a small trust company to a significant player in the financial sector, contributing to the economic development of the region and adapting to industry changes over the decades [1][7]. Group 1: Historical Development - Zhongyuan Trust was established in 1985, marking the revival of the trust industry in China post-reform, and has since been integral to the economic growth of Henan province [2][3]. - The company adopted innovative practices early on, including market-based recruitment and diverse funding methods, which allowed it to support local economic development through loans and investments [3][4]. - Following regulatory reforms in the early 2000s, Zhongyuan Trust expanded its operations significantly, increasing its registered capital from 5.92 billion to 36.5 billion yuan and growing its trust scale from 800 million to 200 billion yuan [4]. Group 2: Recent Developments and Challenges - The introduction of the Asset Management New Regulations in 2018 prompted Zhongyuan Trust to undergo significant organizational adjustments and enhance its business offerings, including the development of a new information system [5][6]. - In 2023, the company completed its largest cash capital increase, raising its registered capital from 4 billion to 4.681 billion yuan, thereby strengthening its financial position [6]. - Zhongyuan Trust has focused on risk management and proactive strategies, enhancing its wealth management and family trust services, while also expanding into digital finance and innovative product offerings [6]. Group 3: Future Outlook - The company has managed over 2 trillion yuan in trust assets and generated significant profits, indicating its robust performance and contribution to the local economy [7]. - As the trust industry undergoes transformation, Zhongyuan Trust aims to enhance its comprehensive strength and maintain its commitment to serving the real economy and improving people's lives [7].

Core Insights - The convertible bond market has become a significant source of excess returns for "fixed income +" fund managers in 2023, with several convertible bond-themed funds reporting returns exceeding 15% year-to-date as of August 8 [1][2] - There is a noticeable divergence in fund managers' strategies regarding convertible bonds, with some reducing their positions while others are increasing them, reflecting a re-evaluation of valuation systems and investment strategies [1][3] Group 1: Performance of Convertible Bonds - Multiple convertible bond-themed funds have performed well in 2023, with specific funds like Southern Changyuan Convertible Bond A and Bosera Convertible Bond Enhanced A achieving returns over 20% [2] - The average price of convertible bonds is currently high, leading to challenges for fund managers in deciding whether to chase high prices or take profits [2][3] Group 2: Fund Manager Strategies - Many fund managers have explicitly stated in their reports that they are reducing their convertible bond positions, with examples including Hai Fu Tong and Hua An Convertible Bond, which saw significant decreases in their convertible bond allocations [3][4] - Conversely, some funds like Fu Guo Convertible Bond and Dongfang Hong Ju Li have increased their convertible bond holdings, indicating a split in strategy among fund managers [3][4] Group 3: Market Dynamics - The convertible bond market is experiencing structural changes due to a decrease in bank convertible bond supply, prompting funds to seek alternative assets to fill the gap in their portfolios [4][5] - The overall allocation to convertible bonds in fixed income portfolios has decreased, with a shift towards sectors like non-bank financials and healthcare [5][6] Group 4: Future Outlook - Fund managers express concerns about the high average prices of convertible bonds, suggesting that the probability of achieving positive returns in the next six months is lower when prices are at current levels [3][4] - Despite the high valuations, some fund managers remain optimistic about the convertible bond market, citing the potential for continued demand driven by favorable equity market conditions [7][8]