Group 1 - June is typically a month of consolidation across various asset classes, including currencies, commodities, and stocks [1] - Historically, the S&P 500 index shows a slight increase of 0.2% in June since 1950 [2] - The first week of June tends to perform strongly, stabilizing in the middle of the month, and then declining towards the end [4] Group 2 - June has been identified as a month with significant factor rotation, with quality, momentum, and size factors performing well, while value factors lag [8] - If seasonal patterns hold, June is expected to favor high-quality large-cap growth stocks, which are positioned at the intersection of all factor tilts [10] Group 3 - The European quality factor may rebound in June, as seasonal factors support long/short quality factor strategies [11] - The healthcare sector has historically performed well in June, with an average increase of 0.8% relative to the S&P 500 index [13] Group 4 - The biotechnology sector is particularly strong seasonally, suggesting that going long on the biotechnology index (XBI) may be the best strategy for the healthcare sector in June [15] - Historically, gold performs poorly in June but marks the end of a seasonal downturn, with significant improvement expected in July [15][17]

Quantitative Factors and Construction Methods Factor Name: BP (Book-to-Price Ratio) - **Construction Idea**: Measures the valuation of a stock by comparing its book value to its market value [13] - **Construction Process**: - Formula: $ BP = \frac{\text{Current Book Value}}{\text{Current Market Value}} $ [13] Factor Name: BP Three-Year Percentile - **Construction Idea**: Evaluates the relative valuation of a stock over the past three years [13] - **Construction Process**: - Formula: BP Three-Year Percentile = Percentile rank of the current BP within the last three years [13] Factor Name: Quarterly EP (Earnings-to-Price Ratio) - **Construction Idea**: Measures the profitability of a stock relative to its market price [13] - **Construction Process**: - Formula: $ \text{Quarterly EP} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] Factor Name: Quarterly EP One-Year Percentile - **Construction Idea**: Tracks the relative profitability of a stock over the past year [13] - **Construction Process**: - Formula: Quarterly EP One-Year Percentile = Percentile rank of the current Quarterly EP within the last year [13] Factor Name: Quarterly SP (Sales-to-Price Ratio) - **Construction Idea**: Measures the revenue generation capability of a stock relative to its market price [13] - **Construction Process**: - Formula: $ \text{Quarterly SP} = \frac{\text{Quarterly Revenue}}{\text{Net Assets}} $ [13] Factor Name: Quarterly SP One-Year Percentile - **Construction Idea**: Tracks the relative revenue generation capability of a stock over the past year [13] - **Construction Process**: - Formula: Quarterly SP One-Year Percentile = Percentile rank of the current Quarterly SP within the last year [13] Factor Name: Small Market Cap - **Construction Idea**: Captures the size effect by focusing on smaller companies [13] - **Construction Process**: - Formula: $ \text{Small Market Cap} = \log(\text{Market Capitalization}) $ [13] Factor Name: 1-Month Reversal - **Construction Idea**: Captures the short-term reversal effect in stock prices [13] - **Construction Process**: - Formula: $ \text{1-Month Reversal} = \text{Cumulative Return over the Last 20 Trading Days} $ [13] Factor Name: Fama-French Three-Factor 1-Month Residual Volatility - **Construction Idea**: Measures the idiosyncratic risk of a stock based on the Fama-French three-factor model [13] - **Construction Process**: - Formula: $ \text{Residual Volatility} = \text{Standard Deviation of Residuals from Fama-French Three-Factor Regression over the Last 20 Trading Days} $ [13] --- Factor Backtesting Results IC Performance - **BP**: Weekly IC = -4.17%, Monthly IC = 0.88%, Yearly IC = 1.86%, Historical IC = 2.19% [9] - **BP Three-Year Percentile**: Weekly IC = -1.08%, Monthly IC = -0.99%, Yearly IC = 2.58%, Historical IC = 1.58% [9] - **Quarterly EP**: Weekly IC = 2.10%, Monthly IC = -0.48%, Yearly IC = -0.46%, Historical IC = 1.18% [9] - **Quarterly EP One-Year Percentile**: Weekly IC = 4.23%, Monthly IC = 3.81%, Yearly IC = 0.98%, Historical IC = 1.73% [9] - **Quarterly SP**: Weekly IC = 0.79%, Monthly IC = 0.93%, Yearly IC = 0.53%, Historical IC = 0.74% [9] - **Quarterly SP One-Year Percentile**: Weekly IC = 4.80%, Monthly IC = 2.82%, Yearly IC = 2.87%, Historical IC = 1.83% [9] - **Small Market Cap**: Weekly IC = 10.49%, Monthly IC = 8.17%, Yearly IC = 3.61%, Historical IC = 2.05% [9] - **1-Month Reversal**: Weekly IC = 7.22%, Monthly IC = 1.22%, Yearly IC = 3.40%, Historical IC = 2.22% [9] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly IC = 3.60%, Monthly IC = 1.11%, Yearly IC = 3.49%, Historical IC = 2.48% [9] Excess Return Performance (Long-Only Portfolio) - **BP**: Weekly Excess Return = -0.83%, Monthly Excess Return = -1.04%, Yearly Excess Return = 3.02%, Historical Cumulative Excess Return = 28.90% [11] - **BP Three-Year Percentile**: Weekly Excess Return = -0.58%, Monthly Excess Return = -1.51%, Yearly Excess Return = 0.97%, Historical Cumulative Excess Return = -3.21% [11] - **Quarterly EP**: Weekly Excess Return = 0.57%, Monthly Excess Return = 1.10%, Yearly Excess Return = 1.44%, Historical Cumulative Excess Return = 30.83% [11] - **Quarterly EP One-Year Percentile**: Weekly Excess Return = -0.01%, Monthly Excess Return = 0.51%, Yearly Excess Return = 3.23%, Historical Cumulative Excess Return = 34.69% [11] - **Quarterly SP**: Weekly Excess Return = -0.01%, Monthly Excess Return = 0.49%, Yearly Excess Return = 0.70%, Historical Cumulative Excess Return = -2.69% [11] - **Quarterly SP One-Year Percentile**: Weekly Excess Return = 0.09%, Monthly Excess Return = 1.25%, Yearly Excess Return = 7.91%, Historical Cumulative Excess Return = 2.23% [11] - **Small Market Cap**: Weekly Excess Return = 0.96%, Monthly Excess Return = 2.76%, Yearly Excess Return = 18.31%, Historical Cumulative Excess Return = 62.57% [11] - **1-Month Reversal**: Weekly Excess Return = 0.83%, Monthly Excess Return = 0.76%, Yearly Excess Return = 3.54%, Historical Cumulative Excess Return = 1.57% [11] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly Excess Return = 0.28%, Monthly Excess Return = 0.75%, Yearly Excess Return = 8.69%, Historical Cumulative Excess Return = 18.67% [11]

Investment Rating - The report gives a "green light" for the short-term outlook of US equities, indicating a positive investment sentiment [2]. Core Insights - The market is experiencing upward momentum until summer technicals and economic data come into play, with investors likely to be halted before any significant drawdown occurs [3]. - Retail investors are actively buying dips in US equities, while institutional activity remains muted [2]. - Robust liquidity is noted, with top of book liquidity at $11.08 million, above the one-year average of $10.65 million, supporting healthy trading in the near term [7][8]. Summary by Sections Market Setup - The report highlights a preference for specific trades, including SPX call spreads and hedging strategies for long positions [5]. - The liquidity environment is described as supportive for trading, although it may lose momentum as summer approaches [8]. Trading Activity - US equities have seen net buying for six consecutive sessions, with a notable increase in long buys, indicating strong market interest [27]. - The overall gross leverage has increased to 289.2%, placing it in the 95th percentile for the past year, driven by short leverage [28][29]. Seasonal Trends - The report notes that early to mid-June typically sees moderate market increases, providing a favorable trading environment, especially for bearish long-term views [64]. ETF Flows - Significant inflows into factor ETFs were observed, with May being the best month for inflows since the election, indicating strong investor interest in momentum strategies [43][50]. - The report also mentions a growing interest from global investors in emerging market equities due to USD weakness and US growth uncertainty [54].

Core Insights - The report explores the construction and application of a style factor system for A-shares, focusing on four dimensions: market capitalization, valuation, profitability, and momentum [2][9][12] - A-shares have exhibited different dominant factors over various periods, with profitability leading from 2013 to 2014, small-cap factors from 2015 to 2016, valuation from 2016 to 2018, and a return to profitability dominance from 2019 to early 2021 [2][24][27] - The report predicts a resurgence of high valuation factors starting in 2025, driven by expectations of weak profit recovery and strong policy support [2][27] Style Factor Construction and Performance - The style factor system is constructed using a bottom-up approach, assigning style labels to each stock based on their factor indicators [9][12] - The performance of the style factors shows that small-cap stocks have generally outperformed large-cap stocks since 2010, with a notable fivefold return from small-cap strategies [12][17] - Valuation factors indicate that low valuation styles have been particularly strong, especially during specific periods such as 2017-2018 and 2022-2024 [14][15] Influencing Factors of Style Factors - Profitability factors are highly correlated with economic cycles, showing better performance during economic upturns [45][46] - Valuation factors are closely linked to market sentiment, with high valuation stocks performing better during periods of positive sentiment [49][50] - Market capitalization factors are significantly influenced by remaining liquidity, with small-cap factors performing strongly in liquidity-rich environments [53][54] Application of Style Factor System - The report establishes an A-share style investment system based on the identified style factors, suggesting that the current dominant styles are high profitability, high valuation, and small-cap [2][27] - The analysis indicates that the A-share market has not fully priced in the expected profit recovery, suggesting potential upside for high profitability and high valuation factors [2][27] - Different asset types exhibit varying dominant style factors, with emerging growth assets showing significant small-cap advantages and dividend assets reflecting low valuation strengths [29][33]

- The PB-ROE-50 portfolio achieved an excess return of 1.15% in the CSI 500 stock pool, 0.29% in the CSI 800 stock pool, and -0.30% in the entire market stock pool[23][24] - The public research stock selection strategy achieved an excess return of 0.54% relative to the CSI 800, while the private research tracking strategy achieved an excess return of 2.61% relative to the CSI 800[25][26] - The block trading portfolio achieved an excess return of -0.61% relative to the CSI All Share Index[29][30] - The directed issuance portfolio achieved an excess return of 0.12% relative to the CSI All Share Index[35][36] - The momentum factor and growth factor achieved positive returns of 0.12% and 0.04% respectively, while the liquidity factor, beta factor, and size factor achieved significant negative returns of -0.56%, -0.52%, and -0.40% respectively[18][20] - In the CSI 500 stock pool, the best-performing factors this week were gross profit margin TTM (1.65%), single-quarter ROA (1.40%), and single-quarter total asset gross profit margin (1.26%)[14][15] - In the liquidity 1500 stock pool, the best-performing factors this week were 5-day average turnover rate (0.45%), 5-minute return skewness (0.36%), and downside volatility ratio (0.33%)[16][17] - In the CSI 500 stock pool, the worst-performing factors this week were single-quarter net profit year-on-year growth rate (-0.42%), 5-day reversal (-0.49%), and post-morning return factor (-0.64%)[14][15] - In the liquidity 1500 stock pool, the worst-performing factors this week were momentum spring factor (-1.07%), 5-day reversal (-1.11%), and single-quarter net profit year-on-year growth rate (-1.19%)[16][17] - In the CSI 300 stock pool, the best-performing factors this week were net profit gap (1.30%), 5-day exponential moving average of trading volume (1.15%), and total asset gross profit margin TTM (1.02%)[12][13] - In the CSI 300 stock pool, the worst-performing factors this week were logarithmic market value factor (-1.02%), momentum spring factor (-1.12%), and post-morning return factor (-1.29%)[12][13] - The net asset growth rate factor performed well in the comprehensive industry, and the net profit growth rate factor performed well in the steel industry[21][22] - The BP factor performed well in the beauty and personal care industry, and the EP factor performed well in the coal industry[21][22]

截至周一收盘，标普500指数较6144.15点的历史收盘高点仅低3%。诚然，引领市场反弹逼近历史高点 的大盘科技股近期可能失去动能。 DataTrek Research联合创始人杰西卡・拉贝（Jessica Rabe）指出，iShares MSCI美国动量因子ETF （MTUM）今年以来表现超过标普500指数10个百分点。从历史来看，在经历如此强劲的上涨后，动量 因子通常会跑输大盘指数。 美国银行指出，其全球股票风险偏好指标已从4月初的"深度恐慌"反弹至中性水平。 该行策略师里特什・萨马迪亚（Ritesh Samadhiya）指出，这一指标在过去38年中已32次从恐慌转向中 性。他补充称，在这些案例中，只有四次市场情绪回落至恐慌水平，"而在所有其他情况下，情绪进一 步上升至乐观水平"。 萨马迪亚表示："在货币宽松背景下，恐慌情绪彻底宣泄后市场广度显著改善，这在历史上通常与新一 轮牛市的延续或形成相关。尽管历史并非完美的指引，但大量证据表明市场可能继续攀升。" 目前来看，美股似乎势不可挡。标普500指数周一小幅收涨，逆转了穆迪下调美债评级引发的跌势，将 连胜纪录延长至六个交易日。这一涨势进一步巩固了该基准指数自 ...

2025 年 4 月 28 日 总量研究 市场波动温和提升，杠铃组合或占优 ——金融工程市场跟踪周报 20250428 要点 上周市场核心观点： 上周（2025.04.21-2025.04.25，下同）A 股窄幅震荡，市场整体表现不佳。主 要宽基指数量能维持近期低位，量能择时指标仍维持谨慎信号。资金面方面，ETF 资金周度净流出，大盘宽基 ETF 为净流出主要方向。市场波动方面，主要宽基 指数截面波动率、时序波动率环比上周皆有上升。 从市场大类因子表现来看，上周市场动量因子占优。结合上证 50 指数层面表现 的相对低迷来看，后市流动性延续宽松背景下，小市值或持续占优。确定性方面， 红利优势仍将维持。"红利+小盘"杠铃组合或为市场探寻方向背景下获取相对 收益的最优选择。 上周市场各指数涨跌不一，上证综指上涨 0.56%，上证 50 下跌 0.33%，沪深 300 上涨 0.38%，中证 500 上涨 1.20%，中证 1000 上涨 1.85%，创业板指上 涨 1.74%，北证 50 指数下跌 2.16%。 截至 2025 年 4 月 25 日，宽基指数来看，上证指数、上证 50、沪深 300、中证 500、中 ...

Report Title - The report is titled "Commodity Quantitative CTA Weekly Tracking" by Guotou Futures Research Institute's Financial Engineering Group, dated March 25, 2025 [1][2] Report Industry Investment Rating - No industry investment rating is provided in the report Core Viewpoints - The commodity sector cross - section has switched, with internal differentiation in the energy and chemical sector, a decline in the agricultural products sector, and the precious metals and non - ferrous sectors remaining relatively strong in the cross - section. Specific sectors show different trends in momentum,持仓量, and term structure [3] Summary by Commodity Categories Overall Commodity Sector - The non - ferrous sector shows upward momentum, while the energy and chemical sector has internal differentiation, the agricultural products sector is down, and the precious metals and non - ferrous sectors are relatively strong. Different sectors have different changes in momentum,持仓量, and term structure indicators [3] Methanol - Strategy net value: The demand factor decreased by 0.23%, the inventory factor decreased by 0.19%, and the synthetic factor weakened by 0.15%. The comprehensive signal this week is neutral. Fundamental factors: The methanol arrival volume gives a long signal, domestic capacity utilization gives a short signal (supply is neutral); methanol - to - olefin plant capacity utilization decreased, acetic acid operating rate increased (demand is neutral); port inventory continued to decrease, and the short - side strength of the inventory factor weakened significantly to neutral; the Inner Mongolia - Shandong regional spread factor gives a long signal, and the spread factor is slightly long [5] Glass - Strategy net value: Last week, the supply factor weakened by 0.20%, the demand factor decreased by 0.19%, the inventory factor decreased by 1.15%, and the synthetic factor weakened by 0.91%. The comprehensive signal this week is short. Fundamental factors: The float glass capacity utilization rate was flat month - on - month (supply is neutral); second - tier city commercial housing transaction data gives a short signal (demand is short); float glass enterprise inventory is relatively high year - on - year (inventory remains short); the domestic float glass market price gives a long signal, but the overall long - side contribution is not high (spread is slightly long) [9] Iron Ore - Strategy net value: The inventory factor weakened by 1.09%, the spread factor remained unchanged, and the synthetic factor weakened by 0.34%. The comprehensive signal this week remains long. Fundamental factors: The iron ore arrival volume at Qingdao Port continued to decline compared with the previous week (supply signal turns neutral); the blast furnace operating rate of 247 steel enterprises increased compared with the previous week (demand signal remains neutral); the inventory of Brazilian iron ore in 31 ports continued to rise (inventory remains long); the spot sales price of Rio Tinto's PB powder at Rizhao Port increased (spread signal remains neutral) [12] Aluminum - Strategy net value: Last week, the supply factor weakened by 0.11%, the demand factor weakened by 0.68%, the inventory factor weakened by 0.12%, the spread factor remained unchanged, and the synthetic factor weakened by 0.20%. The comprehensive signal this week remains long. Fundamental factors: The SMM domestic lead concentrate price continued to rise (supply signal remains long); China's lead alloy exports in March decreased compared with February (demand signal turns short); LME lead registered warrants decreased (inventory turns short); SMM concentrate import profit increased (spread signal is long) [12]

Group 1 - The core viewpoint of the article highlights the recent developments in the U.S. ETF market, particularly the introduction of innovative products such as the Solana futures ETF and the significant inflow of funds into domestic equity products [1][2][3]. Group 2 - The U.S. ETF market saw a total of 10 new products launched last week, with a notable issuance of a municipal bond index product by BlackRock, reflecting strong demand for tax-exempt municipal bonds [1]. - Individual leveraged products have gained popularity, with Defiance and Leverage Shares issuing four 2x leveraged products linked to companies like Robinhood, Palo Alto Networks, and Adobe [1]. - Fortuna launched a Bitcoin strategy product that primarily invests in Bitcoin futures and employs options strategies, including Covered Calls, to provide a safety net [1]. - MarketDesk introduced a high-concentration momentum product that selects stocks based on quality and momentum factors, emphasizing strong performance over the past six months [1]. - Invesco launched a futures strategy product that invests in various futures, including stock index, bond, and foreign exchange futures, with a relatively pessimistic outlook on U.S. stocks [1]. Group 3 - The inflow into U.S. domestic equity products exceeded $60 billion last week, indicating a stabilization in overall U.S. stock performance [3]. - There were significant differences in fund flows among the three major S&P 500 ETFs, with State Street's SPDR S&P 500 ETF experiencing outflows, while Vanguard and BlackRock's products saw substantial inflows [5][8]. - The top inflow products included iShares Core S&P 500 ETF (IVV) with $173.38 million and Vanguard S&P 500 ETF (VOO) with $163.53 million, while SPDR S&P 500 ETF Trust (SPY) faced outflows of $222.23 million [6]. Group 4 - The performance of U.S. ETFs has shifted, with low volatility factors emerging as the strongest performers this year, while growth and quality styles have seen significant pullbacks [9]. - Despite the strong performance of low volatility factors, there has been no significant inflow into these products, whereas dividend products have seen more pronounced inflows [9].

Core Viewpoint - The article discusses the replication and backtesting of a momentum factor based on a report published by Founder Securities, highlighting the efficiency and accuracy of the process in comparison to traditional methods [1][2][3]. Group 1: Data Collection and Challenges - The process involved collecting necessary data for factor calculation, but faced issues with API responses, particularly with Yahoo Finance's support for the Chinese A-share market [2]. - Alternative solutions included creating a simulated dataset and utilizing code found on GitHub to implement factor calculations and backtesting [2]. Group 2: Factor Calculation and Backtesting - The implementation of precise factor calculation code was completed, using simulated data to replace actual data due to difficulties in obtaining historical intraday data for the Chinese A-share market [2]. - A comprehensive quantitative backtesting was conducted to analyze the performance differences between traditional momentum factors and optimal momentum factors [2]. Group 3: Results and Efficiency - The entire replication process was completed successfully, with all conclusions aligning with the original report, taking only 40 minutes under crowded website conditions [3]. - In contrast, a typical employee would require approximately 3 days to complete the same task, while someone unfamiliar with the process might take up to 6 days [3].