- The "ERP and DRP standardized equal-weight calculation model" is used to compute A-share odds, which as of September end, declined to 0.2 standard deviations, indicating a neutral level[10] - The "macro victory rate scoring card model" synthesizes asset victory rates based on factors like credit and PMI pulses, which recently bottomed out, pushing A-share victory rates to 19%[10] - The "bond odds model" is constructed using the expected yield difference between long and short bonds, with recent bond odds retreating to -0.9 standard deviations, reflecting valuation risks for long bonds[11] - The "bond victory rate model" integrates credit and growth expansion data, showing a decline to -6%, indicating low victory rates[11] - The "AIAE indicator model" for US stocks is at 54%, its historical peak, corresponding to 2.4 standard deviations, signaling high pullback risks[15] - The "Federal Reserve liquidity index model" combines quantity and price dimensions, showing a tightening liquidity index at 20%, a medium-high level[15] Model Backtesting Results - ERP and DRP model: A-share odds at 0.2 standard deviations, victory rate at 19%[10] - Bond odds model: -0.9 standard deviations, victory rate at -6%[11] - AIAE indicator model: 54% historical peak, 2.4 standard deviations[15] - Federal Reserve liquidity index: 20% medium-high level[15] Factor Construction and Evaluation - Value factor: High odds (0.9 SD), medium trend (-0.3 SD), low crowding (-1.4 SD), comprehensive score 3, recommended for focus[19][22] - Small-cap factor: Medium odds (-0.2 SD), strong trend (1.6 SD), medium-low crowding (-0.5 SD), comprehensive score 2.2, configuration value improved[20][23] - Quality factor: High odds (1.4 SD), weak trend (-1.2 SD), medium-low crowding (-0.5 SD), comprehensive score 0.6, recommended for long-term attention[24][26] - Growth factor: Medium-high odds (0.8 SD), medium trend (0.1 SD), high crowding (1.0 SD), comprehensive score 0.1, recommended for standard allocation[27][28] Factor Backtesting Results - Value factor: Odds 0.9 SD, trend -0.3 SD, crowding -1.4 SD, score 3[19][22] - Small-cap factor: Odds -0.2 SD, trend 1.6 SD, crowding -0.5 SD, score 2.2[20][23] - Quality factor: Odds 1.4 SD, trend -1.2 SD, crowding -0.5 SD, score 0.6[24][26] - Growth factor: Odds 0.8 SD, trend 0.1 SD, crowding 1.0 SD, score 0.1[27][28] Strategy Construction and Evaluation - "Odds-enhanced strategy" allocates assets based on odds indicators under volatility constraints, achieving annualized returns of 6.6%-7.5% and maximum drawdowns of 2.4%-3.0% since 2011[39][41] - "Victory rate-enhanced strategy" uses macro victory rate scoring to allocate assets, achieving annualized returns of 6.3%-7.7% and maximum drawdowns of 2.3%-2.8% since 2011[42][44] - "Odds + victory rate strategy" combines risk budgets from both strategies, achieving annualized returns of 7.0%-7.6% and maximum drawdowns of 2.7%-2.8% since 2011[45][47] Strategy Backtesting Results - Odds-enhanced strategy: Annualized returns 6.6%-7.5%, max drawdowns 2.4%-3.0%[39][41] - Victory rate-enhanced strategy: Annualized returns 6.3%-7.7%, max drawdowns 2.3%-2.8%[42][44] - Odds + victory rate strategy: Annualized returns 7.0%-7.6%, max drawdowns 2.7%-2.8%[45][47]

Core Insights - The report indicates that the market is currently in an upward trend, with the WIND All A index showing a positive money-making effect of approximately 0.87% [2][10][15] - The report suggests maintaining a portfolio allocation of 80% in absolute return products based on the current valuation levels of the WIND All A index, which is at the 85th percentile for PE and the 50th percentile for PB, indicating a moderate valuation [11][8] Market Overview - The WIND All A index experienced a slight decline of 0.18% over the past week, with small-cap stocks represented by the CSI 2000 down by 0.02%, mid-cap stocks in the CSI 500 up by 0.32%, and large-cap indices like the CSI 300 and SSE 50 down by 0.44% and 1.98% respectively [9][10] - The report highlights strong performance in sectors such as power equipment and new energy, with new energy stocks rising by 3.61%, while the banking sector saw a decline of 4.09% [9][10] Timing System Analysis - The distance between the short-term (20-day) and long-term (120-day) moving averages continues to widen, indicating a sustained upward trend in the market, with the latest figures showing a 13.57% difference [2][10] - The report emphasizes that as long as the money-making effect remains positive, there is potential for continued inflow of incremental funds into the market [2][10][15] Sector Recommendations - The report recommends focusing on sectors that are likely to benefit from policy-driven growth, including innovative pharmaceuticals, new energy, and chemicals, while also suggesting a renewed focus on precious metals [2][10][15] - The TWO BETA model continues to recommend technology sectors, particularly in computing power and consumer electronics [2][10][15]

Group 1 - The report indicates that the current WIND All A index is in an upward trend, with the trend line positioned around 6106 points and a positive earning effect of approximately 1.9% [2][10] - The report suggests maintaining a balanced allocation in response to increased market volatility, especially as the market enters a significant event window [2][10] - The report highlights that the market's short-term moving average (20-day) is above the long-term moving average (120-day), with the distance between them increasing from 12.15% to 13.19%, indicating a continued upward trend [2][9] Group 2 - The industry allocation model recommends focusing on sectors that are expected to benefit from policy-driven growth, such as chemicals and innovative new energy, while also continuing to support the Hong Kong innovative pharmaceutical sector [2][10] - The report emphasizes the importance of the market's earning effect in sustaining mid-term incremental capital inflows, as long as the earning effect remains positive [2][10] - The report identifies technology sectors, particularly those related to computing power and batteries, as areas of interest based on the TWO BETA model [2][10]

Core Insights - The report indicates that the market is in an upward trend, with the WIND All A index showing a significant distance of 12.15% between the short-term (20-day) and long-term (120-day) moving averages, suggesting a continued bullish environment [2][4][11] - The current market environment is characterized by a positive profit effect of 1%, and as long as this remains positive, there is potential for continued inflow of incremental funds [2][4][11] - The report highlights the importance of maintaining a balanced portfolio due to increased market volatility, recommending adjustments to holdings in favor of defensive sectors [3][4][11] Market Performance - The WIND All A index experienced a decline of 1.37% over the past week, with small-cap stocks (CSI 2000) down 1.72%, mid-cap stocks (CSI 500) down 1.85%, and large-cap stocks (CSI 300) down 0.81% [10] - Notable sector performance included a 5.91% increase in the electric equipment and new energy sector, while the defense and military sector saw a decline of 11.61% [10] Investment Strategy - The report recommends maintaining a high position in the market, suggesting an 80% allocation to absolute return products based on the current market conditions [3][11] - The industry allocation model suggests a focus on sectors that are likely to benefit from policy support, such as chemicals, non-ferrous metals, and innovative new energy, while also recommending investments in Hong Kong innovative pharmaceuticals and securities insurance [3][4][11] - The report advises against chasing high-flying stocks and instead suggests increasing exposure to previously lagging sectors to mitigate risks during market adjustments [3][4][11]

Group 1 - The article discusses a macro quantitative framework that combines economic, liquidity, credit, and inflation factors for asset allocation and industry/style configuration [1][3] - The framework has been adjusted based on the changing mapping of macro variables to assets, with a focus on economic and liquidity indicators [1][5] - The performance of aggressive portfolios since 2013 shows an annualized return of approximately 8.5%, with a 0.6% excess return compared to the benchmark [3][5] Group 2 - The article highlights the impact of macroeconomic conditions on industry and style configurations, incorporating credit sensitivity into the analysis [5][7] - The macro-sensitive industry configuration has shown varying performance, with a notable decline since 2022, indicating the need for adjustments in selection criteria [7][10] - The article emphasizes the importance of market expectations in influencing macroeconomic indicators and their relationship with asset performance [13][18] Group 3 - The Factor Mimicking model is introduced to capture market expectations regarding macro variables, using a refined stock pool for better representation [19][20] - The construction of the Factor Mimicking portfolio aims to reflect the market's implicit views on economic, liquidity, inflation, and credit variables [19][23] - The article discusses the need for additional micro mappings to enhance the representation of macro variables, particularly in relation to corporate earnings and valuations [28][30] Group 4 - The article outlines the adjustments made to the macro variables based on market expectations, focusing on economic, liquidity, and credit dimensions [34][36] - The revised indicators are expected to improve asset allocation strategies, particularly in the context of equity markets [39][40] - The performance of the revised industry and style configurations indicates a positive impact from incorporating market expectations into the analysis [46][54]

Core Insights - The report emphasizes a bullish market sentiment, suggesting that investors should continue to accumulate positions during dips as long as the market maintains a positive profit effect [1][2][3] - The current profit effect value is reported at 5.22%, indicating a strong market environment, and the recommendation is to hold high positions until the profit effect turns negative [2][10] - The report identifies key sectors for investment, including innovative pharmaceuticals and securities insurance, which are expected to benefit from ongoing upward trends [2][10] Market Overview - The Wind All A index is currently in an upward trend, with the short-term moving average (20-day) at 5752 points and the long-term moving average (120-day) at 5271 points, resulting in a distance of 9.12% between the two [2][10] - The overall market saw significant gains, with the Wind All A index rising by 3.87% last week, and small-cap stocks (CSI 2000) increasing by 3.23% [1][9] - The report highlights strong performance in the telecommunications and electronics sectors, with telecommunications stocks rising by 10.47% [1][9] Investment Strategy - The report recommends maintaining an 80% position in absolute return products based on the Wind All A index, as the current PE ratio is at the 85th percentile, indicating a moderate valuation level [3][10] - The focus for mid-term investments should be on sectors that are expected to experience a turnaround, particularly innovative pharmaceuticals and securities insurance, alongside policy-driven sectors like photovoltaics and chemicals [2][10] - The Two Beta model continues to recommend technology sectors, specifically military computing and battery technologies, while short-term signals suggest a potential rebound for gold stocks after adjustments [2][10]

Group 1 - The report indicates a marginal increase in trading activity in the A-share market, with the average daily trading volume rising to 2.1 trillion yuan, and the turnover rate for the Shanghai Composite Index reaching 93% [2][14][20] - The report highlights a decrease in the proportion of stocks that are rising, which has dropped to 54.4%, while the median weekly return for all A-shares has decreased to 0.4% [2][15] - The report notes that the industry rotation index has shown a marginal increase, with 13 industries having turnover rates above the historical 90th percentile [2][27] Group 2 - The report tracks liquidity in the A-share market, noting an increase in ETF outflows and a shift to foreign capital inflows, with foreign capital inflowing 2.65 million USD [2][43][44] - Public funds have seen a decrease in newly established fund sizes, dropping to 5.947 billion yuan, while the overall stock positions of funds have increased [2][36] - Private equity confidence has shown a slight recovery, with the private equity fund confidence index increasing, although the overall positions have slightly decreased [2][41][42] Group 3 - The report indicates a clear divergence in capital allocation, with foreign capital flowing out of the household appliance and machinery sectors while primarily flowing into the metals sector [2][3][44] - The report highlights that the top sectors for financing inflows include electronics (+13.27 billion yuan) and machinery (+4.01 billion yuan), while coal (-0.23 billion yuan) and textiles (-0.01 billion yuan) have seen outflows [2][26] - The report also notes that the top sectors for ETF inflows include food and beverage (+0.59 billion yuan) and coal (+0.46 billion yuan), while electronics (-18.06 billion yuan) and computers (-3.90 billion yuan) have seen significant outflows [2][26] Group 4 - The report mentions that southbound capital inflows have increased, with net purchases rising to 38.12 billion yuan, marking a significant percentile since 2022 [5][4] - The report states that the Hang Seng Index rose by 1.7%, reflecting a general upward trend in global markets, with major markets showing positive performance [5][4] - The report indicates that global foreign capital has marginally flowed into developed markets, with the US and UK seeing the largest inflows, while China also experienced a net inflow of 5.6 million USD [5][4]

Core Viewpoint - The A-share market has reached a historic milestone, with the total market capitalization surpassing 100 trillion yuan for the first time, driven by significant increases in various sectors, particularly the information technology sector [1][8]. Market Performance - On August 18, the Shanghai Composite Index opened high and broke through the previous high of 3731.69 points, marking a ten-year high since August 2015 [1]. - The total market capitalization of A-shares reached 100.19 trillion yuan, an increase of 14.33 trillion yuan since the beginning of the year [1]. - The total trading volume for the year has reached 223.65 trillion yuan, with an average daily trading volume of 1.47 trillion yuan [1]. Sector Performance - The information technology sector has seen a market capitalization increase of 11.55% since August, making it the largest contributor to the overall market capitalization growth [7]. - Other sectors such as materials and industrials also experienced significant growth, with market capitalization increases of 7.10% and 6.54%, respectively [7]. - The financial sector maintained a strong position with a market capitalization of 177.02 trillion yuan, reflecting a 3.39% increase [7]. Investor Behavior - There is a notable influx of retail investors into the market, although their overall participation remains cautious due to a prevailing "fear of heights" sentiment [8][9]. - New individual investor accounts have shown marginal improvement since May, but the absolute numbers remain low, indicating a lack of significant capital inflow from retail investors [8][9]. - The trend of "capital migration" among residents is expected to continue, with a decrease in the attractiveness of low-interest savings and financial products, potentially leading to increased investment in the stock market [10]. Future Outlook - Institutional funds are anticipated to continue flowing into A-shares, with foreign capital shifting from net selling to net buying [10]. - The report suggests focusing on three investment directions: technology sectors such as consumer electronics and AI software, new consumption trends, and thematic investments like commercial aerospace and brain-computer interfaces [10].

Quantitative Models and Construction Methods 1. Model Name: Timing System Signal (Wind All A Moving Average Distance Model) - **Model Construction Idea**: This model uses the distance between the short-term moving average (20-day) and the long-term moving average (120-day) of the Wind All A Index to determine the market's overall trend. A positive and expanding distance indicates an upward trend[2][9]. - **Model Construction Process**: 1. Calculate the 20-day moving average (short-term) and the 120-day moving average (long-term) of the Wind All A Index. - Latest values: 20-day MA = 5658, 120-day MA = 5241[2][9]. 2. Compute the percentage difference between the two moving averages: $ \text{Distance} = \frac{\text{20-day MA} - \text{120-day MA}}{\text{120-day MA}} \times 100\% $ - Current distance = 7.96%[2][9]. 3. Interpret the signal: If the distance is greater than 3% and positive, the market is in an upward trend[2][9]. - **Model Evaluation**: The model effectively captures the market's upward momentum and provides a clear signal for maintaining high equity positions during positive trends[2][9]. 2. Model Name: Industry Allocation Model - **Model Construction Idea**: This model identifies industries with potential for medium-term outperformance based on factors such as policy support, valuation, and growth trends[2][10]. - **Model Construction Process**: 1. Analyze industry-specific drivers, including policy incentives and growth catalysts. 2. Identify sectors with "distressed reversal" characteristics or benefiting from policy-driven growth. 3. Recommend sectors such as innovative pharmaceuticals, securities insurance, photovoltaics, coal, and non-ferrous metals. 4. Use the TWO BETA model to emphasize technology-related sectors, including military, computing power, and batteries[2][10]. - **Model Evaluation**: The model provides actionable insights for sector rotation, aligning with macroeconomic and policy trends[2][10]. 3. Model Name: Position Management Model - **Model Construction Idea**: This model determines optimal equity allocation levels based on valuation metrics and market trends[3][10]. - **Model Construction Process**: 1. Assess valuation levels of the Wind All A Index using PE and PB ratios. - Current PE: 70th percentile (moderate level). - Current PB: 30th percentile (low level)[3][10]. 2. Combine valuation analysis with timing signals (e.g., moving average distance and profit-making effect). 3. Recommend equity allocation levels based on the above factors. - Current recommendation: 80% equity allocation[3][10]. - **Model Evaluation**: The model balances valuation and trend analysis, providing a systematic approach to equity allocation[3][10]. --- Model Backtesting Results 1. Timing System Signal - Moving average distance: 7.96% (greater than the 3% threshold, indicating an upward trend)[2][9]. 2. Industry Allocation Model - Recommended sectors: Innovative pharmaceuticals, securities insurance, photovoltaics, coal, non-ferrous metals, military, computing power, and batteries[2][10]. 3. Position Management Model - PE: 70th percentile (moderate level)[3][10]. - PB: 30th percentile (low level)[3][10]. - Recommended equity allocation: 80%[3][10]. --- Quantitative Factors and Construction Methods 1. Factor Name: Profit-Making Effect - **Factor Construction Idea**: This factor measures the market's ability to generate profits for investors, serving as a key indicator of market sentiment and potential capital inflows[2][10]. - **Factor Construction Process**: 1. Calculate the profit-making effect value based on market performance. - Current value: 3.73% (positive)[2][10]. 2. Interpret the signal: A positive value indicates sustained investor confidence and potential for further capital inflows[2][10]. - **Factor Evaluation**: The factor is a reliable indicator of market sentiment, supporting timing and allocation decisions[2][10]. --- Factor Backtesting Results 1. Profit-Making Effect - Current value: 3.73% (positive, indicating sustained market confidence)[2][10].

- The report defines the market environment using the distance between the long-term (120-day) and short-term (20-day) moving averages of the WIND All A index, which continues to expand, indicating an upward trend [2][9][10] - The industry allocation model recommends sectors such as innovative drugs in Hong Kong and securities for mid-term allocation, while the TWO BETA model continues to recommend the technology sector, focusing on military and computing power [2][3][10] - The current PE ratio of the WIND All A index is around the 70th percentile, indicating a moderate level, while the PB ratio is around the 30th percentile, indicating a relatively low level [3][10][15] Model and Factor Construction 1. **Model Name: Industry Allocation Model** - **Construction Idea**: Recommends sectors based on mid-term market trends - **Construction Process**: Utilizes historical data and market trends to identify sectors with potential for reversal and growth, such as innovative drugs and securities in the Hong Kong market - **Evaluation**: Effective in identifying sectors with potential for mid-term growth [2][3][10] 2. **Model Name: TWO BETA Model** - **Construction Idea**: Focuses on sectors with high beta values, indicating higher volatility and potential returns - **Construction Process**: Analyzes sectors with high beta values, recommending technology, military, and computing power sectors - **Evaluation**: Continues to recommend high-growth sectors, showing consistency in sector selection [2][3][10] Model Backtesting Results 1. **Industry Allocation Model** - **PE Ratio**: 70th percentile [3][10][15] - **PB Ratio**: 30th percentile [3][10][15] - **Moving Average Distance**: 6.92% [2][9][10] - **Profitability Effect**: 2.30% [2][9][10] 2. **TWO BETA Model** - **PE Ratio**: 70th percentile [3][10][15] - **PB Ratio**: 30th percentile [3][10][15] - **Moving Average Distance**: 6.92% [2][9][10] - **Profitability Effect**: 2.30% [2][9][10]