Market Overview - The market is currently in a state of stock game with significant funding divergence, as indicated by the liquidity shock index for the CSI 300, which was -0.49 last Friday, lower than the previous week at 0.49, suggesting current market liquidity is above the average level of the past year by -0.49 standard deviations [1] - The PUT-CALL ratio for the SSE 50 ETF options has been rising, reaching 0.83 last Friday, up from 0.67 the previous week, indicating increased caution among investors regarding the short-term performance of the SSE 50 ETF [1] - The average turnover rates for the SSE Composite Index and Wind All A-shares were 1.38% and 1.94%, respectively, indicating a decrease in trading activity, positioned at the 78.04% and 81.46% percentile since 2005 [1] Macro Factors - The RMB exchange rate fluctuated last week, with onshore and offshore rates showing weekly declines of -0.42% and -0.2%, respectively [1] - The U.S. stock market experienced a downward trend, with the Dow Jones Industrial Average, S&P 500, and Nasdaq indices reporting weekly returns of -0.9%, -2.12%, and -3.23% [1] - The National Bureau of Statistics reported that profits of large-scale industrial enterprises in China reached 1.02 trillion yuan in January-February 2026, a year-on-year increase of 15.2%, accelerating by 14.6 percentage points compared to the previous year [1] Market Sentiment - The A-share market experienced some fluctuations and divergence last week, with heightened risk aversion due to ongoing geopolitical tensions, which have suppressed short-term risk appetite [1] - Technical analysis indicates multiple intraday reversals in the A-share market, suggesting significant funding divergence and a stock game state, leading to a low probability of upward trends in the short term [1] Factor Analysis - The overall market PE (TTM) stands at 22.5 times, positioned at the 77.5% percentile since 2005 [2] - The small-cap factor's congestion level has decreased to -0.11, while the low valuation factor's congestion level is at -0.54, indicating a shift in market dynamics [2] - Industry congestion levels are relatively high in sectors such as comprehensive, communication, non-ferrous metals, basic chemicals, and oil & petrochemicals, with the latter two sectors showing a significant increase in congestion [2]

Core Viewpoint - The A-share market is expected to remain in a state of fluctuation in the short term, as indicated by various technical and quantitative indicators [1][2]. Market Overview - During the week of March 16-20, 2026, the Shanghai Composite Index fell by 2.47%, the CSI 300 Index decreased by 2.19%, the CSI 500 Index dropped by 5.82%, while the ChiNext Index rose by 1.26% [3]. - The current overall market PE (TTM) stands at 22.6 times, which is at the 78.3% percentile since 2005 [3]. - Historical data shows that the CSI 500 Index has performed well in the latter half of March since 2005 [3]. Factor Crowding Observation - The small-cap factor crowding has increased, with a current value of 0.09. The low valuation factor crowding is at -0.31, while the high profitability factor crowding is at 0.24, and the high profitability growth factor crowding is at 0.25 [3]. Industry Crowding - Industries such as comprehensive, communication, non-ferrous metals, steel, and electronics exhibit relatively high crowding levels. The oil and petrochemical, as well as agriculture, forestry, animal husbandry, and fishery industries have seen a significant increase in crowding [4].

Quantitative Models and Construction Methods 1. Model Name: Sentiment Model - **Model Construction Idea**: The sentiment model is designed to measure the strength of market sentiment using factors related to limit-up and limit-down events[4][13] - **Model Construction Process**: The model uses factors such as net limit-up ratio, next-day return after limit-down, limit-up ratio, limit-down ratio, and high-frequency board-hitting returns to quantify sentiment. Each factor is scored, and the overall sentiment score is calculated on a scale of 0 to 5[13][17] - **Model Evaluation**: The sentiment model score is currently 0, indicating weak market sentiment[13][17] 2. Model Name: Trend Model - **Model Construction Idea**: The trend model identifies market trends by analyzing technical indicators and price movements[4][13] - **Model Construction Process**: The model uses the SAR (Stop and Reverse) indicator to detect trend reversals. For example, the Wind All-A Index broke below the SAR indicator on March 3, signaling a negative trend[13][14] - **Model Evaluation**: The trend model currently emits a negative signal, indicating a bearish market trend[13] 3. Model Name: Weighted Model - **Model Construction Idea**: The weighted model combines multiple signals, including sentiment and trend, to provide a comprehensive market outlook[4][13] - **Model Construction Process**: The weighted model aggregates signals from the sentiment and trend models, assigning weights to each component. The current weighted model signal is negative, reflecting overall bearishness in the market[13] - **Model Evaluation**: The model effectively integrates multiple signals but currently indicates a negative market outlook[13] 4. Model Name: High-Frequency Capital Flow Model - **Model Construction Idea**: This model uses high-frequency capital flow data to generate buy/sell signals for major broad-based indices[4][13] - **Model Construction Process**: The model tracks capital flow trends for indices such as CSI 300, CSI 500, CSI 1000, and CSI 2000. Signals are categorized into aggressive long, aggressive short, conservative long, and conservative short. For the week, all indices (CSI 300, CSI 500, CSI 1000, CSI 2000) showed negative signals (-1 for aggressive short and conservative short)[13][17] - **Model Evaluation**: The model provides timely signals for broad-based indices but currently reflects a bearish sentiment across all indices[13][17] --- Model Backtesting Results 1. Sentiment Model - Sentiment score: 0 (out of 5)[13][17] 2. Trend Model - SAR indicator: Negative signal for Wind All-A Index[13][14] 3. Weighted Model - Weighted signal: Negative[13] 4. High-Frequency Capital Flow Model - CSI 300: Aggressive short (-1), Conservative short (-1)[13][17] - CSI 500: Aggressive short (-1), Conservative short (-1)[13][17] - CSI 1000: Aggressive short (-1), Conservative short (-1)[13][17] - CSI 2000: Aggressive short (-1), Conservative short (-1)[13][17] --- Quantitative Factors and Construction Methods 1. Factor Name: Small-Cap Factor - **Factor Construction Idea**: Measures the performance of small-cap stocks and their crowding level[18][19] - **Factor Construction Process**: The factor's crowding level is calculated using metrics such as valuation spread, pairwise correlation, market volatility, and return reversal. The composite crowding score is 0.09[18][19] - **Factor Evaluation**: The small-cap factor shows a slight increase in crowding, indicating moderate interest from investors[18][19] 2. Factor Name: Low-Valuation Factor - **Factor Construction Idea**: Tracks the performance of low-valuation stocks and their crowding level[18][19] - **Factor Construction Process**: The factor's crowding level is calculated using the same metrics as the small-cap factor. The composite crowding score is -0.31[18][19] - **Factor Evaluation**: The low-valuation factor shows a decrease in crowding, suggesting reduced investor interest[18][19] 3. Factor Name: High-Profitability Factor - **Factor Construction Idea**: Measures the performance of high-profitability stocks and their crowding level[18][19] - **Factor Construction Process**: The factor's crowding level is calculated using the same metrics as the small-cap factor. The composite crowding score is 0.24[18][19] - **Factor Evaluation**: The high-profitability factor shows moderate crowding, indicating stable investor interest[18][19] 4. Factor Name: High-Growth Factor - **Factor Construction Idea**: Tracks the performance of high-growth stocks and their crowding level[18][19] - **Factor Construction Process**: The factor's crowding level is calculated using the same metrics as the small-cap factor. The composite crowding score is 0.25[18][19] - **Factor Evaluation**: The high-growth factor shows moderate crowding, reflecting steady investor interest[18][19] --- Factor Backtesting Results 1. Small-Cap Factor - Composite crowding score: 0.09[18][19] 2. Low-Valuation Factor - Composite crowding score: -0.31[18][19] 3. High-Profitability Factor - Composite crowding score: 0.24[18][19] 4. High-Growth Factor - Composite crowding score: 0.25[18][19]

Investment Rating - The report maintains a neutral investment rating for the A-share market, indicating that it is currently difficult to break the oscillating pattern in the short term, but there may be potential for a rebound due to some macroeconomic indicators showing signs of recovery [1][7]. Core Insights - The A-share market continues to exhibit a volatile pattern, with the Shanghai Composite Index down by 1.2% and the CSI 300 Index up by 0.19% over the past week. The current market PE (TTM) stands at 23.3 times, which is at the 81.9% percentile since 2005 [7][9]. - Liquidity indicators based on the CSI 300 Index show a liquidity shock index of 0.41, significantly higher than the previous week's 0.05, indicating that current market liquidity is above the average level of the past year [8]. - The report highlights a cautious sentiment among investors, as evidenced by the rising PUT-CALL ratio for the SSE 50 ETF, which reached 0.94, up from 0.73 the previous week [8]. - Macro factors indicate a mixed picture, with February CPI rising to 1.3% year-on-year, exceeding both the previous value of 0.2% and the consensus forecast of 0.88%. Meanwhile, PPI showed a year-on-year decline of -0.9%, better than the previous -1.4% [9][10]. Summary by Sections Market Overview - The A-share market remains in a state of oscillation, with the potential for a rebound as some macroeconomic indicators show recovery. The market's trading activity has increased, with the average turnover rates for the Shanghai Composite Index and Wind All A Index at 1.56% and 2.13%, respectively, both at high percentiles since 2005 [7][8]. Factor Crowding Observation - The report notes a continued decline in the crowding of small-cap factors, with a crowding score of -0.14. Low valuation factors also show a crowding score of -0.32, while high profitability and high growth factors have scores of 0.20 and 0.29, respectively [16][18]. Industry Crowding - The report identifies high crowding levels in the industries of comprehensive, non-ferrous metals, communication, basic chemicals, and steel. The crowding in the oil and petrochemical and agriculture, forestry, animal husbandry, and fishery sectors has increased significantly [20][23].

Investment Rating - The report indicates a neutral investment rating for the A-share market, suggesting that the current oscillating pattern is unlikely to break in the short term [1][7]. Core Insights - The market sentiment has weakened according to the sentiment model, but the trend model continues to signal positively. The moving average strength index has significantly declined, yet there remains a distance to the bottom. The high-frequency capital flow model still indicates a negative signal, reinforcing the view that the current oscillating pattern in the A-share market is difficult to break in the short term [1][7][12]. - The liquidity shock indicator based on the CSI 300 index was 0.05, lower than the previous week (0.92), indicating that current market liquidity is above the average level of the past year by 0.05 standard deviations [8][11]. - The PUT-CALL ratio for the Shanghai 50 ETF options has decreased to 0.73 from 0.84, reflecting an increased optimism among investors regarding the short-term performance of the Shanghai 50 ETF [8][11]. - The five-day average turnover rates for the Shanghai Composite Index and the Wind All A Index are 1.62% and 2.24%, respectively, indicating increased trading activity [8][11]. Summary by Sections Market Overview - The Shanghai 50 Index fell by 1.54%, the CSI 300 Index by 1.07%, the CSI 500 Index by 3.44%, and the ChiNext Index by 2.45% during the week of March 2 to March 6, 2026. The overall market PE (TTM) stands at 23.4 times, at the 82.3 percentile since 2005 [7][9]. - Historical data shows that the ChiNext Index and the Shanghai 50 have performed well in the first half of March since 2005 [9]. Factor Crowding Observation - The small-cap factor crowding has decreased, with a score of -0.06. The low valuation factor crowding is at -0.67, while the high profitability factor crowding is at 0.13, and the high growth factor crowding is at 0.21 [17][19]. Industry Crowding - The report identifies high crowding in the following sectors: comprehensive, non-ferrous metals, basic chemicals, telecommunications, and steel. The crowding in the oil and petrochemical and agriculture, forestry, animal husbandry, and fishery sectors has increased significantly [21][24].

Quantitative Models and Construction Methods 1. Model Name: Sentiment Model - **Model Construction Idea**: The sentiment model is designed to measure the strength of market sentiment by analyzing factors such as the proportion of limit-up and limit-down stocks, and the profitability of high-frequency trading strategies[12][16] - **Model Construction Process**: The sentiment model is built using factors related to market sentiment, including: - Proportion of net limit-up stocks - Next-day returns of limit-down stocks - Proportion of limit-up stocks - Proportion of limit-down stocks - Returns of high-frequency trading strategies The model assigns scores to these factors, with a maximum score of 5. The sentiment model score for the current period is 0[12][16] - **Model Evaluation**: The sentiment model indicates a weakening of market sentiment, as reflected by the score of 0[12][16] 2. Model Name: Trend Model - **Model Construction Idea**: The trend model aims to capture the directional movement of the market by analyzing price trends and other technical indicators[12] - **Model Construction Process**: The trend model generates signals based on the analysis of market trends. For the current period, the trend model provides a positive signal, indicating an upward trend in the market[12] - **Model Evaluation**: The trend model continues to emit positive signals, suggesting a favorable market trend[12] 3. Model Name: High-Frequency Capital Flow Model - **Model Construction Idea**: This model uses high-frequency capital flow data to generate buy and sell signals for major broad-based indices[12][16] - **Model Construction Process**: The model evaluates the capital flow trends for indices such as CSI 300, CSI 500, CSI 1000, and CSI 2000. The signals are categorized as aggressive long, aggressive short, conservative long, and conservative short. For the current period, the model emits negative signals for all indices[12][16] - **Model Evaluation**: The high-frequency capital flow model continues to emit negative signals, indicating a bearish outlook for the indices[12][16] --- Model Backtesting Results 1. Sentiment Model - Sentiment model score: 0 (out of 5)[12][16] 2. Trend Model - Trend model signal: Positive[12] 3. High-Frequency Capital Flow Model - CSI 300: Aggressive short (-1), Conservative short (-1)[12][16] - CSI 500: Aggressive short (-1), Conservative short (-1)[12][16] - CSI 1000: Aggressive short (-1), Conservative short (-1)[12][16] - CSI 2000: Aggressive short (-1), Conservative short (-1)[12][16] --- Quantitative Factors and Construction Methods 1. Factor Name: Small-Cap Factor - **Factor Construction Idea**: Measures the performance and crowding of small-cap stocks[17][19] - **Factor Construction Process**: The small-cap factor's crowding is assessed using four metrics: - Valuation spread - Pairwise correlation - Market volatility - Return reversal The composite score for the small-cap factor is -0.06[17][19] - **Factor Evaluation**: The small-cap factor shows a slight decline in crowding, as indicated by the composite score[17][19] 2. Factor Name: Low-Valuation Factor - **Factor Construction Idea**: Evaluates the performance and crowding of low-valuation stocks[17][19] - **Factor Construction Process**: The low-valuation factor's crowding is assessed using the same four metrics as the small-cap factor. The composite score for the low-valuation factor is -0.67[17][19] - **Factor Evaluation**: The low-valuation factor exhibits a higher level of crowding, as reflected by the negative composite score[17][19] 3. Factor Name: High-Profitability Factor - **Factor Construction Idea**: Measures the performance and crowding of high-profitability stocks[17][19] - **Factor Construction Process**: The high-profitability factor's crowding is assessed using the same four metrics. The composite score for the high-profitability factor is 0.13[17][19] - **Factor Evaluation**: The high-profitability factor shows a moderate level of crowding, with a positive composite score[17][19] 4. Factor Name: High-Growth Factor - **Factor Construction Idea**: Evaluates the performance and crowding of high-growth stocks[17][19] - **Factor Construction Process**: The high-growth factor's crowding is assessed using the same four metrics. The composite score for the high-growth factor is 0.21[17][19] - **Factor Evaluation**: The high-growth factor demonstrates a relatively low level of crowding, as indicated by the positive composite score[17][19] --- Factor Backtesting Results 1. Small-Cap Factor - Composite crowding score: -0.06[17][19] 2. Low-Valuation Factor - Composite crowding score: -0.67[17][19] 3. High-Profitability Factor - Composite crowding score: 0.13[17][19] 4. High-Growth Factor - Composite crowding score: 0.21[17][19]

Market Overview - The A-share market is currently in a consolidation phase, with structural opportunities being the main focus [1][2] - The technical sentiment model continues to signal positively, while the moving average strength index has shown an upward trend without indicating a peak [2] - High-frequency capital flow models are still signaling negatively [2] Quantitative Indicators - The liquidity shock indicator for the CSI 300 index was 0.92, lower than the previous week (2.52), indicating current market liquidity is 0.92 standard deviations above the average level over the past year [2] - The PUT-CALL ratio for the SSE 50 ETF decreased to 0.84 from 0.91, suggesting reduced caution among investors regarding the short-term performance of the SSE 50 ETF [2] - The five-day average turnover rates for the SSE Composite Index and the Wind All A Index were 1.31% and 1.91%, respectively, indicating increased trading activity [2] Macro Factors - The RMB exchange rate fluctuated last week, with onshore and offshore exchange rates increasing by 0.8% and 0.52%, respectively [2] - The overall market PE (TTM) stands at 23.7 times, which is at the 83.1% percentile since 2005 [3] Factor Crowding - The crowding degree for small-cap factors has increased, with a crowding degree of 0.14 for small-cap factors, -0.58 for low valuation factors, -0.13 for high profitability factors, and 0.14 for high profitability growth factors [3] Industry Crowding - The crowding degree is relatively high in the comprehensive, non-ferrous metals, basic chemicals, telecommunications, and electronics sectors, with significant increases in crowding for the steel and building materials industries [4]

Core Viewpoint - The article suggests that mid-cap stocks, particularly the CSI 500 index, may initiate an upward trend following the Chinese New Year, despite negative signals from major indices based on technical analysis [1][2]. Market Overview - In the pre-holiday period (February 9-13, 2026), the Shanghai Composite Index decreased by 0.12%, while the CSI 300 Index increased by 0.36%. The CSI 500 Index rose by 1.88%, and the ChiNext Index increased by 1.22% [3]. - The current market PE (TTM) stands at 23.2 times, which is at the 81.5% percentile since 2005 [3]. - Historical data indicates that the CSI 500 and ChiNext indices have performed well in the five trading days following the Chinese New Year since 2005 [3]. Quantitative Indicators - The liquidity shock indicator for the CSI 300 Index was 2.52 on Friday, lower than the previous week’s 6.21, indicating current market liquidity is 2.52 times the average level over the past year [2]. - The PUT-CALL ratio for the Shanghai 50 ETF options decreased to 0.91 from 0.96, suggesting reduced caution among investors regarding the short-term outlook for the Shanghai 50 ETF [2]. - The five-day average turnover rates for the Shanghai Composite Index and Wind All A were 1.10% and 1.70%, respectively, indicating a decline in trading activity [2]. Macro Factors - The onshore and offshore RMB exchange rates experienced a weekly increase of 0.41% [2]. - January's CPI in China was reported at 0.2% year-on-year, lower than the previous value of 0.8% and the expected 0.44% [2]. - The PPI year-on-year was -1.4%, better than the previous -1.9% and the expected -1.45% [2]. - New RMB loans in January amounted to 4.71 trillion yuan, exceeding the expected 4.50 trillion yuan and the previous 679.4 billion yuan [2]. - M2 money supply grew by 9% year-on-year, surpassing the expected 8.41% and the previous 8.5% [2]. Industry Insights - The article notes that the industry crowding degree is relatively high in sectors such as comprehensive, non-ferrous metals, basic chemicals, telecommunications, and electronics, with significant increases in the crowding degree for comprehensive and retail sectors [4].

- The report discusses the **high-frequency capital flow model**, which indicates that signals for major broad-based indices remain negative. This model is used to generate buy and sell signals for indices like CSI 300, CSI 500, CSI 1000, and CSI 2000. The signals for all these indices are currently negative, suggesting a cautious market sentiment[4][13][17] - The **sentiment model** is also highlighted, which measures market sentiment strength using factors such as net limit-up ratio, next-day return after limit-down, and high-frequency board-hitting returns. The sentiment model score is 2 out of 5, indicating a moderate sentiment level. The trend model signal is positive, while the weighted model signal is negative[13][17] - The **factor crowding analysis** is presented, which evaluates the crowding level of factors like small-cap, low-valuation, high-profitability, and high-growth. The crowding scores are calculated using metrics such as valuation spread, pairwise correlation, long-term return reversal, and factor volatility. The composite crowding scores are as follows: small-cap (0.03), low-valuation (-0.40), high-profitability (0.03), and high-growth (0.50)[18][20] - The **liquidity shock indicator** for the CSI 300 index is mentioned, with a value of 2.52, indicating that current market liquidity is 2.52 standard deviations above the past year's average. This suggests improved liquidity conditions in the market[4][8] - The **put-call ratio** for the SSE 50 ETF options is reported to be 0.91, lower than the previous week's 0.96, reflecting a decrease in short-term caution among investors regarding the SSE 50 ETF[4][8] - The **turnover rates** for the SSE Composite Index and Wind All A Index are 1.10% and 1.70%, respectively, corresponding to the 70.18% and 75.99% percentiles since 2005. This indicates a decline in trading activity[4][8] - The **calendar effect** analysis shows that since 2005, the CSI 500 and ChiNext indices have performed well in the five trading days following the Chinese New Year, with average returns of 3.73% and 2.58%, respectively. The probability of positive returns during this period is 81% for the CSI 500 and 80% for the ChiNext[7][10][15] - The **industry crowding analysis** identifies sectors such as comprehensive, non-ferrous metals, basic chemicals, communication, and electronics as having relatively high crowding levels. The comprehensive and retail sectors show the largest increases in crowding compared to the previous month[22][24][25]

Group 1 - The core viewpoint of the article indicates that the market is expected to continue its oscillation in the upcoming week, based on various technical indicators and market sentiment models [1][2]. - The liquidity shock indicator for the CSI 300 index was reported at 6.21, which is higher than the previous week's 5.07, suggesting that current market liquidity is significantly above the average level over the past year [2]. - The PUT-CALL ratio for the SSE 50 ETF increased to 0.96 from 0.89, indicating a rising caution among investors regarding the short-term performance of the SSE 50 ETF [2]. Group 2 - The Shanghai Composite Index and Wind All A five-day average turnover rates were recorded at 1.34% and 1.97%, respectively, indicating a decrease in trading activity, positioned at the 77.24% and 82.76% percentiles since 2005 [2]. - The official manufacturing PMI for China in January was reported at 49.3, lower than the previous value of 50.1 and below the consensus expectation of 50.18, while the S&P Global China Manufacturing PMI was at 50.3, slightly above the previous value [2]. - The SAR indicator showed that the Wind All A index broke below the reversal indicator on February 2, indicating a potential downward trend [2]. Group 3 - The A-share market experienced fluctuations last week, with the SSE 50 index down by 0.93%, the CSI 300 index down by 1.33%, the CSI 500 index down by 2.68%, and the ChiNext index down by 3.28% [3]. - The current overall market PE (TTM) stands at 23.0 times, which is at the 81.0% percentile since 2005, indicating a relatively high valuation level [3]. - Observations on factor crowding indicate a decrease in high profitability factor crowding, with small-cap factor crowding at 0.06 and low valuation factor crowding at -0.31 [3].