Investment Rating - The report maintains a "Buy" rating for the coal sector, highlighting strong price recovery and supply constraints as key factors for investment opportunities [3][4][15]. Core Views - Coal prices have accelerated unexpectedly, with supply constraints continuing to support price increases. The report anticipates that coal prices may exceed 900 RMB/ton by the end of the year due to seasonal demand and supply-side restrictions [2][10]. - The report emphasizes the importance of high spot price elasticity stocks, recommending specific companies based on their performance and growth potential in the current market environment [3][15]. Summary by Sections Industry Overview - As of October 12, coal production from 442 mines in Shanxi, Shaanxi, and Inner Mongolia was 26.77 million tons, down 4.1% year-on-year and 1.0% month-on-month, indicating a consistent decline in supply [1][9]. - The report notes that since July 2025, the monthly coal production has seen a year-on-year decline of over 3%, with further reductions expected due to safety inspections and production checks [1][9]. Price Trends - The report highlights that coal prices rebounded sharply post-National Day, contrary to expectations of a seasonal decline, primarily driven by supply-side constraints [2][10]. - The report forecasts that non-electric demand, particularly from the coal chemical sector, will increase, providing additional support for coal prices [2][10]. Investment Recommendations - Recommended stocks include: 1. High spot price elasticity stocks: Lu'an Environmental Energy [3][15]. 2. Stable growth stocks: Jinko Coal Industry, Huayang Co., Ltd. [3][15]. 3. Stocks with recovery potential: Shanxi Coal International [3][15]. 4. Industry leaders: China Shenhua, China Coal Energy, Shaanxi Coal Industry [3][15]. 5. Beneficiaries of nuclear power growth: CGN Mining [3][15]. Company Performance - The report provides earnings forecasts and valuations for key companies, indicating a positive outlook for their performance in the coming years [4][15]. - The coal sector has shown resilience, with the CITIC coal sector index rising 4.3% in the week ending October 17, outperforming the broader market indices [16][18].

Investment Rating - The report maintains a "Buy" recommendation for key companies in the oil and gas sector, specifically China National Petroleum Corporation, China Petroleum & Chemical Corporation, China National Offshore Oil Corporation, Zhongman Petroleum, and New Natural Gas [4]. Core Views - The geopolitical premium on crude oil has weakened, with OPEC+ supply dominating in the short term. The report highlights that despite pressures on oil prices due to increased OPEC+ production, there remains a bottom support for prices [1][8]. - The report suggests that the market's main influences on oil prices are the geopolitical situation in the Middle East and the supply intensity from OPEC+, rather than the recent developments in U.S.-China trade tensions or India's oil import policies [1][8]. Summary by Sections Industry Dynamics - As of October 17, the U.S. dollar index decreased to 98.55, while Brent crude oil futures settled at $61.29 per barrel, down 2.30% week-on-week, and WTI futures at $57.54 per barrel, down 2.31% [2][9]. - U.S. crude oil production rose to 13.64 million barrels per day, an increase of 10,000 barrels from the previous week, while refinery throughput decreased to 15.13 million barrels per day, down 117,000 barrels [10][11]. Company Performance - The report forecasts earnings per share (EPS) for key companies: China National Petroleum Corporation (0.90 CNY for 2024), China National Offshore Oil Corporation (2.90 CNY for 2024), and China Petroleum & Chemical Corporation (0.41 CNY for 2024) [4]. - The report indicates that the petrochemical sector is experiencing a "de-involution" policy, recommending attention to industry leaders with stable performance and high dividends, such as China National Petroleum and China Petroleum & Chemical [3][11]. Market Trends - The report notes that the oil and gas sector has seen a decline of 2.8% as of October 17, underperforming the broader market indices [12][16]. - The report highlights that the refining sub-sector had the highest weekly increase of 0.2%, while other petrochemical sub-sectors experienced declines, with the largest drop being 7.9% [16][17].

Investment Rating - The report maintains a "Recommended" rating for the company [4][6]. Core Views - The company demonstrated resilience in its operations, with Q3 2025 revenue reaching 5.04 billion yuan, a year-on-year increase of 29.6%, despite a quarter-on-quarter decline of 10.0% [2]. - The growth in revenue is attributed to the significant increase in two-wheeler exports and the rapid growth of the "Jike" electric motorcycle sales [2][3]. - The company is expected to continue its long-term growth trajectory, particularly in two-wheeler exports and high-end four-wheeler market positioning [4]. Summary by Sections Financial Performance - For the first three quarters of 2025, the company achieved a total revenue of 14.9 billion yuan, up 30.1% year-on-year, and a net profit attributable to shareholders of 1.42 billion yuan, up 30.9% year-on-year [1]. - In Q3 2025, the net profit was 410 million yuan, reflecting a year-on-year increase of 10.8% but a quarter-on-quarter decrease of 30.5% [2]. Two-Wheeler Segment - The sales of mid-to-large displacement motorcycles increased significantly, with a total of 142,000 units sold from January to August 2025, representing a year-on-year growth of 41.6% [3]. - The "Jike" electric motorcycle brand saw sales of 193,000 units in the same period, marking a substantial year-on-year increase [3]. Four-Wheeler Segment - The company sold 122,000 all-terrain vehicles in the first eight months of 2025, a year-on-year increase of 6.7% [4]. - The company is focusing on expanding its presence in the U.S. market and enhancing its high-end product offerings [4]. Future Projections - Revenue projections for 2025, 2026, and 2027 are estimated at 19.91 billion yuan, 24.51 billion yuan, and 29.50 billion yuan, respectively, with net profits expected to reach 1.86 billion yuan, 2.38 billion yuan, and 2.93 billion yuan [5][11]. - The earnings per share (EPS) are projected to be 12.19 yuan, 15.61 yuan, and 19.21 yuan for the same years [5][11].

Investment Rating - The report maintains a "Recommended" rating for the company [6]. Core Views - The company is expected to achieve a net profit attributable to shareholders of 15.2-16.2 billion yuan for the first three quarters of 2025, representing a year-on-year increase of 69.1%-80.3% [1]. - The growth is driven by multiple business collaborations, with significant contributions from the Wujie brand and the all-terrain vehicle segment [1][4]. - The company has expanded its domestic and international sales channels, with a notable increase in export sales [2]. Summary by Sections Performance Overview - The company forecasts a net profit of 5.0 billion yuan for Q3 2025, a year-on-year increase of 60.5% [1]. - The sales volume of mid-to-large displacement motorcycles (over 250cc) reached 28,000 units in July-August, up 22.1% year-on-year [1]. - The all-terrain vehicle sales increased by 40.7% year-on-year, with the new XWolf1000 model contributing to the growth [1]. Brand Development - The Wujie brand achieved a revenue of 1.98 billion yuan in H1 2025, a 30.2% increase year-on-year, with exports accounting for 60.1% of sales [2]. - The brand's sales network expanded to 1,053 domestic outlets and 1,292 overseas outlets, with a significant presence in Europe [2]. Market Expansion - The sales of mid-to-large displacement motorcycles in 2024 and H1 2025 were 108,000 and 68,000 units, respectively, with exports showing strong growth [3]. - The Wujie brand has made significant inroads in the European market, with notable sales increases in Spain and Italy [3]. Financial Projections - Revenue projections for 2025-2027 are 20.16 billion, 23.41 billion, and 27.05 billion yuan, respectively, with net profits of 1.98 billion, 2.32 billion, and 2.71 billion yuan [4][5]. - The expected earnings per share (EPS) for 2025, 2026, and 2027 are 0.96, 1.13, and 1.32 yuan, respectively [5].

Revenue and Fiscal Analysis - The U.S. government is projected to have a fiscal revenue of $5.23 trillion for FY 2025, an increase of approximately $310 billion compared to FY 2024, largely due to tariff revenue contributing about $120 billion, a growth of approximately 150%[3] - Fiscal spending is expected to grow by 4%, with net interest payments exceeding $1 trillion for the first time, leading to an increase in the deficit by $110 billion compared to FY 2024[4] Tax and Tariff Challenges - The "OBBBA" tax reduction effects are anticipated to be contractionary in 2025, with significant impacts expected only in 2026, while potential legal challenges to tariffs could reduce revenue by at least $200 billion annually[4] - Tariff revenues from April to September 2025 are estimated at around $90 billion, which could be reversed if tariffs are deemed illegal[4] Revenue Generation Strategies - The administration is focusing on "opening up new sources of revenue" by increasing tariffs and pricing public goods, such as defense spending, to generate income[5] - Innovative strategies include government equity stakes in companies, export fees on sensitive products, and transaction fees for government-facilitated deals, exemplified by a proposed 15% fee on AI chip exports to China[7][8] Immigration and Visa Fees - The introduction of high fees for immigration services, such as $1 million for a green card and $100,000 for H-1B visas, could generate an estimated additional revenue of $7.7 billion annually[8] Economic Implications - The administration's approach reflects a shift towards "state capitalism," where government support for industries translates into revenue-sharing arrangements, potentially impacting long-term economic growth expectations[9] - The strategy aims to balance inflation and debt management while maintaining a weak dollar and long-term U.S. Treasury yields as market characteristics[10]

Group 1 - The liquidity perspective indicates that after the National Day holiday, the funding environment has returned to a loose state, with overnight funding rates dropping below 7DOMO and 7-day funding rates around 7DOMO, alleviating pressure on banks' liabilities [1][9] - The report anticipates that the government bond supply pressure in the fourth quarter will be manageable, with limited government bond issuance currently affecting the funding environment [1][9] - The upcoming tax period is expected to maintain a comfortable funding state before its arrival, with overall pressure from the upcoming reverse repos being manageable due to the five working days for operations [1][9] Group 2 - As of October 19, the issuance progress of local government bonds shows that cumulative replacement bonds issued reached 19,900 billion yuan, achieving 99.50% progress; new general bonds issued totaled 6,717 billion yuan, achieving 83.97% progress; and new special bonds issued reached 36,973 billion yuan, achieving 84.03% progress [2][10] - The report notes that the issuance of local bonds has sharply decreased post-National Day, leading to a decline in secondary market transactions, with significant drops in net purchases by insurance and participation from funds in the 7-10 year segment [3][11] - The fourth quarter local bond issuance plan is set at 8,516 billion yuan, with expectations of around 10,000 billion yuan in market neutral expectations, although no incremental policy reserves have been observed [2][11] Group 3 - The report highlights opportunities in local bonds from three perspectives: the implied tax rates for 5Y and 10Y bonds remain around 5%, while most 20Y and 30Y bonds are below 4% [3][12] - The report suggests monitoring specific bonds with high implied tax rates, such as the 25 Tianjin bond with an implied tax rate of 12.21%, despite its small issuance size [3][12] - The report also notes that the yield spread between local bonds and government bonds has widened, particularly in the 7Y and 10Y segments, indicating a need to pay attention to risks associated with long-duration bonds [3][12]

Report Industry Investment Rating No relevant information provided. Core Viewpoints of the Report - T0 strategies, with low risk exposure and high return - drawdown ratios, are attracting more attention. Stock T0 strategies have an annualized return of 5% - 20% and a drawdown of around 1%, making them popular as alternative absolute - return strategies. Futures T0 strategies are more advantageous carriers, offering high liquidity, low costs, and leverage, and having lower slippage compared to commodity futures [1]. - Combining deep - learning - based medium - low - frequency momentum/reversal strategies is a viable approach for futures T0 strategies. The K - Shape algorithm is used to classify intraday trends into three types: upward, downward, and sideways. An MLP + GRU neural network is used to predict these trends, with a validation set win - rate increasing from 33% to 40%. By integrating these predictions with an intraday CTA base strategy, the strategy can achieve a post - fee annualized return of 11.19% and a drawdown of 3.62%, and over 30% annualized return on the IM contract [2][3][4]. Summary According to the Table of Contents 1. Analysis of the Characteristics of Futures T0 Strategies 1.1 From Stock T0 to Futures T0 Strategies - **Stock T0 Strategies**: T0 strategies are less affected by index trends and macro - economic conditions, and more related to turnover and intraday amplitude. They can be divided into manual and programmed T0. Their annualized returns range from 5% to 20%, with small drawdowns, and are suitable for small - scale funds or large - position strategies. There are already mature third - party algorithm providers collaborating with brokerages [9][12][13]. - **Advantages of Futures T0 Strategies**: Futures offer a T + 0 trading mechanism, high liquidity, sufficient amplitude, low trading costs, and leverage. They also have lower slippage compared to commodity futures, providing a better platform for T0 strategies [16][18]. - **Significance for Multi - asset and Multi - strategy Allocation**: Futures T0 strategies can diversify asset allocation, provide free leverage and short - side returns, and improve the performance of traditional asset portfolios. For example, adding a CTA - like strategy to a basic asset pool can increase the annualized return of a risk - parity strategy from 5.50% to 6.67% and reduce the maximum drawdown from 6.71% to 3.74% [19][21]. 1.2 Exploration of Futures T0 Strategy Paradigms - **Differences from Traditional Strategies**: T0 strategies have time - limited opening and closing positions, a narrowing decision - making space, and are highly susceptible to high - frequency information flows, requiring strict trading discipline [23]. - **Specific Implementation Logics**: - **Micro - structure Strategies Based on Order Books**: Analyze high - frequency data such as order book volume and price distribution to predict short - term price trends, with high trading frequencies [25]. - **Momentum/Reversal and Statistical Arbitrage Strategies**: Based on financial time - series statistical laws, with medium - low trading frequencies. Momentum strategies follow trends, while reversal strategies capture corrective rebounds [26]. - **Combination of Machine/Deep Learning with Traditional Paradigms**: Machine and deep learning can automatically learn complex non - linear patterns from large - scale, high - dimensional, and noisy data, and are used in the above two types of strategies [27]. 2. T0 Framework Based on Intraday Trend Pattern Prediction 2.1 Review of Time - Series Clustering Algorithms - **DTW + K - Means**: DTW can measure the similarity between time series, overcoming translation, scaling, and periodic invariance. Combined with K - Means, it can cluster intraday index trends, but is affected by outliers and has high computational complexity [33][39][40]. - **K - Shape**: A time - series clustering algorithm using shape - based distance (SBD) to measure similarity, with translation and scaling invariance. It has better computational efficiency and cluster - center representation, and is used for subsequent analysis [41]. 2.2 Clustering Performance of the K - Shape Algorithm on Stock Index Spot - The K - Shape algorithm is used to cluster the intraday trends of the Shanghai 50, CSI 300, CSI 500, and CSI 1000. Initially, 20 - category clustering is performed, and then reduced to 8 categories. The cluster centers are explicitly initialized, and the final three - category classification (upward, downward, and sideways) is used for subsequent prediction [48][51][53]. 2.3 Prediction of Trend Pattern Labels Based on Deep Learning - For medium - low - frequency T0 strategies, predicting trend types is more meaningful than predicting returns. An MLP neural network with a Softmax output layer is used, integrating cross - sectional and time - series price - volume features. The validation set win - rate can increase from 12.5% to 20.35%, and for the three - category classification, it can increase from 33% to 40%. The model is retrained quarterly to ensure stable performance [57][58][65]. 2.4 T0 Baseline Strategy: Intraday ATR Breakout - The intraday ATR breakout strategy is a trend - following strategy that uses the previous day's ATR to set trading intervals, with opening, stop - profit, and stop - loss thresholds. It is sensitive to trading fees. Under a unilateral fee rate of 0.0025%, the CSI 300, CSI 500, and CSI 1000 can achieve positive long - term returns [72][75][80]. 2.5 Futures T0 Strategy Based on Trend Pattern Prediction - By predicting intraday trends, the application and parameters of the base strategy can be adjusted. For example, on four equal - weighted contracts from January 2023 to June 2025, the annualized return can increase from 6.65% to 11.19%, and the maximum drawdown can be reduced from 7.45% to 3.62% [84][86][87]. 2.6 Summary and Outlook - Futures T0 strategies are more advantageous than stock T0 strategies, and an intraday trend pattern prediction + intraday CTA framework is used to construct the strategy. Future research can focus on improving trend prediction by adding more information and developing reversal CTA strategies [92][93][96].

Report Industry Investment Rating The provided content does not mention the report industry investment rating. Core Viewpoints of the Report - The current tariff upgrade is likely to follow the pattern of April 2025, with smaller market fluctuations. Trump's subsequent remarks have shown signs of moderation, and the market may have a strong learning effect from the previous negotiation model. As a result, market volatility may be lower and the recovery may be faster in this round of trade frictions. In the short term, it strengthens the long - end bullish momentum of US Treasuries [3][17]. Summary by Relevant Catalogs 1. Review of Market Feedback Patterns in Previous Trade Frictions - **2018.03 - 2018.06: Gradual Recognition Stage at the Beginning of Trade Frictions** - In March 2018, the US announced steel and aluminum tariffs and planned to impose tariffs on $60 billion worth of Chinese goods. Initially, the scope was relatively narrow, and the impact on the global market was not significant. - Over the next three months, as the market recognized the threat of trade frictions, the Chinese equity market was under pressure, with the Shanghai Composite Index falling about 11.45% cumulatively. The bond market strengthened due to risk - aversion sentiment, and the yield of 10 - year Treasury bonds declined by about 19bp, showing a "strong bonds, weak stocks" pattern [1][9]. - **2019.05 - 2019.12: Global Resonance Stage with Re - emergence of Conflicts** - In May 2019, Sino - US negotiations broke down, and trade conflicts escalated again after a brief cease - fire. - Against the backdrop of high trade environment uncertainty and the global manufacturing PMI entering the bottom cycle, most global markets were in a "strong bonds, weak stocks" seesaw pattern in the second half of 2019. The yield of 10 - year US Treasuries dropped from 2.45% to around 1.74% within three months [1][12]. - **2025.04: Amplification and Rapid Recovery of Impact from "Reciprocal Tariffs"** - On April 2, 2025, Trump announced the "reciprocal tariff" policy, imposing a "reciprocal tariff" starting at 10% on all countries. This tariff had an unexpected magnitude and also targeted non - Chinese countries, causing a global impact. - The market reacted quickly. Within five days, major global stock indices fell between 5 - 15%. Funds flocked to "safe - haven" bonds. The yield of 10 - year Japanese Treasury bonds declined by about 32bp within five days, and safe - haven currencies such as the yen and Swiss franc strengthened. - After several rounds of negotiations, the stock market rebounded significantly, and the market gradually alleviated concerns about tariffs. The trading sentiment became relatively insensitive to marginal changes in tariff policies, reaching a consensus of "high - opening and low - running tariffs." The main stock indices basically recovered to pre - tariff levels, while the bond market showed differentiated performance due to factors such as fundamentals, inflation expectations, and political situations [2][14]. 2. This Week's Overseas Macroeconomic Interest Rate Review 2.1 Macroeconomic Indicator Comments - As of the week ending October 3, driven by rising production and increased imports, US EIA crude oil inventories continued to rise after the previous week's rebound. The change in US EIA crude oil inventories for the week was 3.715 million barrels, higher than the forecast of 2.25 million barrels and the previous value of 1.792 million barrels. Despite the larger - than - expected increase in inventories, concerns about Russian crude oil supply disruptions and the recovery of US demand boosted market sentiment to some extent, causing oil prices to rise slightly one hour after the data release [18]. 2.2 Review of Main Overseas Market Interest Rates - **US**: Trade frictions may intensify, and US Treasury yields are falling rapidly. This week (October 3 - October 10, 2025), US Treasury yields declined. Trump's tariff threat on Friday led to pressure on the US stock market, with the Nasdaq Index dropping 3.56% in a single day, the largest decline since April. The yield of 10 - year US Treasuries dropped 9bp in a single day, and COMEX gold rose 1.58% to $4035.5 per ounce. As the government shutdown may continue and trade frictions may re - emerge, funds are expected to further flow into the bond market. The recent unexpected increase in short - term debt issuance may imply a reduction in long - term debt issuance in November, which is beneficial for lowering long - end market interest rates [19]. - **Auction Results**: The 3 - year US note auction was neutral to robust, the 10 - year US note auction was weak, and the 30 - year US Treasury auction was relatively robust [22]. - **Europe and Japan**: - **Japan**: Under the expectation of "pro - stimulus" policies, the yield of long - term Japanese bonds is approaching a 17 - year high. The yield of 10 - year Japanese bonds is stable at around 1.70%, close to the highest level since 2008. However, the breakdown of the Japanese ruling coalition on Friday makes the future policy direction uncertain [30]. - **Germany**: German bond yields declined overall this week [30]. 3. Comments on Other Major Asset Classes - **Equity**: Vietnam and Japan reached new highs, while European and American markets generally weakened. Vietnam's VN30 had the strongest performance (+6.51%), followed by Japan's Nikkei 225 (+5.07%). European, American, and Hong Kong markets generally declined. The political turmoil in Paris led to a significant decline in the French stock market, and Trump's threat against China pressured the US stock market [31]. - **Commodities**: Safe - haven precious metals and base metals were strong, while energy, agricultural products were weak, and crypto - assets tumbled. Gold and silver prices rose significantly, driven by risk - aversion demand and a weaker US dollar. Base metals and energy raw materials also generally strengthened. In contrast, Brent crude oil, agricultural products, and Bitcoin declined [32]. - **Foreign Exchange**: The Russian ruble led the gains, and the Japanese yen led the losses. The ruble rose 1.73%, while the yen fell 3.63% due to easing expectations [33]. 4. Market Tracking The report provides data on the changes in bond yields, stock index returns, commodity price changes, and foreign exchange rate fluctuations of major global economies this week, as well as the latest economic data panels of the US, Japan, and the Eurozone [39][48][55][59].

Group 1: Trade Performance Overview - In September, China's exports increased by 8.3% year-on-year (in USD), up 3.9 percentage points from the previous month[4] - Imports rose by 7.4% year-on-year (in USD), an increase of 6.1 percentage points compared to August[4] - The overall trade data for September exceeded expectations, indicating a potential for sustained recovery despite ongoing trade tensions with the US[5] Group 2: Export Dynamics - The growth in exports is supported by diversification into non-US markets and upgrades in the industrial chain, with significant contributions from the EU and emerging economies[5] - High-tech products, including integrated circuits and transportation equipment, led the export growth, reflecting a shift towards higher value-added sectors[6] - The "de-involution" policy has positively impacted export prices, with noticeable price recovery in steel and electronics, while labor-intensive products saw price declines[6] Group 3: Import Insights - The surge in import growth was primarily driven by rising international commodity prices, particularly in technology-related sectors like aircraft and integrated circuits[7] - Although there was a marginal recovery in the import of raw materials, the increase was largely price-driven rather than volume-driven, indicating potential short-term volatility[7] - The sustainability of the import growth remains uncertain, as domestic demand recovery appears weak[7] Group 4: Risks and Considerations - Future risks include potential policy changes that may not meet expectations and unexpected shifts in the domestic economic landscape[8] - Export fluctuations could also pose risks to the overall trade outlook, necessitating close monitoring of external factors[8]

- **Quantitative model and construction method** - **Model name**: Three-dimensional timing framework - **Model construction idea**: The model integrates liquidity, divergence, and prosperity indicators to assess market trends and provide timing signals [7][11][12] - **Model construction process**: 1. **Liquidity index**: Calculated based on market trading volume and other liquidity-related metrics [18] 2. **Divergence index**: Measures the degree of disagreement among market participants [16] 3. **Prosperity index**: Reflects the overall economic and market health, scaled to match the dimension of the Shanghai Composite Index [20] 4. Combine the three indices into a unified framework to evaluate market conditions and predict trends [12] - **Model evaluation**: The model maintains a stable performance in predicting market trends, with historical data showing its effectiveness in identifying periods of market oscillation and downturns [14] - **Quantitative factor and construction method** - **Factor name**: Growth factor - **Factor construction idea**: Measures the growth potential of stocks based on financial metrics such as revenue and profit growth [39][40] - **Factor construction process**: 1. Calculate the growth rate of key financial metrics, such as revenue, profit, and liabilities [42][44] 2. Normalize the metrics by market capitalization and industry to ensure comparability [41] 3. Construct the factor by aggregating the normalized metrics into a composite score [42][44] - **Factor evaluation**: The growth factor demonstrated positive returns, with high-growth stocks outperforming low-growth stocks in the recent week [40][42] - **Factor name**: Size factor - **Factor construction idea**: Evaluates the performance of stocks based on their market capitalization [39] - **Factor construction process**: 1. Divide stocks into groups based on market capitalization [39] 2. Calculate the average return for each group [39] 3. Compare the performance of large-cap stocks against small-cap stocks [39] - **Factor evaluation**: Large-cap stocks outperformed small-cap stocks, with the size factor recording positive returns [39] - **Factor name**: Beta factor - **Factor construction idea**: Measures the sensitivity of stocks to market movements [40] - **Factor construction process**: 1. Calculate the beta of each stock based on historical price movements relative to the market [40] 2. Group stocks into high-beta and low-beta categories [40] 3. Compare the performance of high-beta stocks against low-beta stocks [40] - **Factor evaluation**: High-beta stocks outperformed low-beta stocks, with the beta factor recording positive returns [40] - **Factor name**: Alpha factors (multiple) - **Factor construction idea**: Focuses on growth-related metrics and analyst adjustments to predict stock performance [42][46] - **Factor construction process**: 1. Calculate metrics such as single-quarter ROE growth, revenue growth, and analyst forecast adjustments [42][46] 2. Normalize these metrics by market capitalization and industry [41] 3. Aggregate the metrics into individual alpha factors [42][46] - **Factor evaluation**: Alpha factors such as single-quarter ROE growth and analyst forecast adjustments showed strong performance, particularly in small and mid-cap stocks [46][47] - **Model backtesting results** - **Three-dimensional timing framework**: Historical performance indicates stable prediction of market oscillations and downturns [14] - **Factor backtesting results** - **Growth factor**: Weekly long-side excess return of 0.42% [40] - **Size factor**: Weekly long-side excess return of 1.57% [39] - **Beta factor**: Weekly long-side excess return of 1.08% [40] - **Alpha factors**: - Single-quarter ROE growth (considering quick reports and forecasts): Weekly excess return of 1.61%, monthly excess return of 10.17% [44][47] - Analyst forecast adjustment (np_FY1): Weekly excess return of 7.14% in CSI 300, 5.60% in CSI 500, 9.54% in CSI 1000, and 4.19% in CSI 2000 [47] - Single-quarter ROE growth (report): Weekly excess return of 7.47% in CSI 300, 3.84% in CSI 500, 8.11% in CSI 1000, and 3.09% in CSI 2000 [47]