Group 1 - Current A-share market sentiment is at a historically high level, characterized by liquidity, asset pricing differences, and trading activity [1] - Several industries, including chemicals, building materials, light manufacturing, machinery, defense, automotive, home appliances, textiles, non-bank financials, electronics, communications, computers, and media, are triggering congestion indicators [1] - A high number of industries are in a sustained congestion state, indicating potential for market adjustments [1] Group 2 - A-share market showed strong fluctuations with sectors like liquor, non-ferrous metals, communication equipment, and aerospace performing well, while electronic chemicals, automotive, beauty care, and utilities lagged [2] - There is a notable shift of household savings towards capital markets, providing a continuous source of incremental funds [2] - The overall profit growth expectation for A-share listed companies is projected to turn positive by 2025, ending a four-year decline, with significant elasticity in the technology innovation sector [2] Group 3 - Following stabilization of overseas liquidity disturbances, the A-share market continued its trend of rising volume and price, with the Shanghai Composite Index nearing 3900 points and total market turnover exceeding 30 trillion [3] - There is a focus on the rotation opportunities in recently popular sectors and potential rebounds in relatively low-positioned sectors supported by recent policies [3] - The "anti-involution" policy and demand-side policies are expected to significantly influence the A-share market, with household savings entering the market being a crucial support for index strength [3]

Group 1: Liquidity and Fund Flows - Leverage funds continue to flow in, with net inflow of margin financing at approximately 288 billion CNY, maintaining a high level[9] - Southbound funds have seen a cumulative net inflow exceeding 270 billion CNY over the past three months, with weekly averages above 10 billion CNY[8] - The total net inflow of public equity funds increased to 105.4 billion CNY, up from 91.9 billion CNY[10] Group 2: Trading Activity and Market Sentiment - Trading heat in the military industry rose by 16 percentage points to 85%, while the semiconductor sector increased by 5 percentage points to 90%[4] - The Shanghai Composite Index reached a new high for the year, contributing to a slight increase in A-share search activity on social media platforms[7] - Retail investor net inflow decreased to 1,032.5 billion CNY, down by 316.2 billion CNY from the previous value, representing 52.1% of the past five years[4] Group 3: Sector Performance - The electronics sector saw a net inflow of 56 billion CNY, while the banking sector experienced a net outflow of 14.2 billion CNY[21] - The stock market's ETF saw a net outflow of 54.6 billion CNY, indicating a low sentiment level, positioned at the 23.8% percentile over the past three years[22] - The total amount of stock buybacks increased to 41.4 billion CNY, up from 36 billion CNY, reflecting an 85% percentile over the past three years[25]

Market Sentiment - The A-share market sentiment index has shown a slight decline but remains in an optimistic range, with trading congestion levels showing divergence and overall levels being relatively high [1][10] - The market sentiment reached its highest level of the year due to factors such as easing Middle Eastern geopolitical risks and expectations surrounding "anti-involution" policies, approaching the peak seen in July 2020 [1][11] - However, as policy expectations cool and overseas equity markets experience significant adjustments, the A-share market sentiment is trending downward, with the 5-day moving average of the sentiment index falling below the 20-day moving average [1][11] Earnings Expectations - The earnings expectations for A-shares remain weak, with the consensus net profit growth forecast for the CSI 300 index at 0.7%, down 2.8 percentage points from 2024 [3][4] - Despite a low base for earnings last year, the profit growth forecast for small-cap indices in 2025 is still low [3] - Economic stimulus is likely to increase in the second half of the year, which may help offset the impact of weak external demand and trade frictions, but the overall offsetting effect is expected to be moderate [3] Liquidity Environment - The liquidity environment remains supportive, with stock ETFs experiencing a net outflow of approximately 4.9 billion yuan, although the outflow scale is gradually shrinking [7][10] - Northbound capital saw a net inflow of around 4.7 billion yuan, marking a shift from previous net outflows [7][10] - Retail investors continue to show strong buying interest, with a net inflow of approximately 35.1 billion yuan, marking 12 consecutive weeks of net inflows [7][10] Trading Congestion - Trading congestion levels in the A-share market are showing significant divergence, with some indices experiencing rising congestion while others see a decline [10] - The trading congestion for indices like the CSI 1000 and CSI 2000 has notably increased, while indices such as the CSI 300 and SSE 50 have seen a decrease [10] - Overall, while trading sentiment has surpassed the high point of October 2024, there is still a notable gap in trading congestion levels, indicating that bullish trading has not yet reached a significantly overheated state [10]

Group 1: Capital Flow and Liquidity - Southbound funds have seen a cumulative net inflow of over 250 billion yuan in the past three months, with weekly net inflows exceeding 10 billion yuan[14] - Retail investors contributed a net inflow of 134.86 billion yuan in the last week, marking a 22.5 billion yuan increase from the previous value, maintaining a high level at the 76.4 percentile over the past five years[8] - Leverage funds continue to flow in at high levels, with net inflows of approximately 322.8 billion yuan last week, although this is a decrease from the previous week's 446.1 billion yuan[30] Group 2: Market Trends and Investor Sentiment - The Shanghai Composite Index experienced its first decline after five consecutive weeks of increases, indicating a potential shift in market sentiment[8] - The trading heat for the machinery sector increased by 29 percentage points to 86%, while the construction sector rose by 24 percentage points to 72%[9] - The search interest in A-shares has declined, reflecting a cooling investor sentiment despite high net inflows from retail investors[8] Group 3: ETF and Fund Performance - The net subscription for stock ETFs dropped significantly to -38.13 billion yuan, a stark contrast to the previous net inflow of -5.3 billion yuan, placing it at the 1.9 percentile over the past three years[42] - The issuance of new public equity funds decreased to 9.21 billion yuan, which is at the 46 percentile over the past three years, indicating a contraction in new fund launches[50] - The total amount of share buybacks increased to 3.6 billion yuan, up from 1.85 billion yuan, reflecting a strong buyback trend at the 78 percentile over the past three years[46]

Group 1: Fund Liquidity - Southbound funds have seen a cumulative net inflow of over 250 billion CNY in the past three months, with weekly net inflows exceeding 10 billion CNY[5] - Leverage funds continue to see high net inflows, with net inflow of 322.8 billion CNY last week, maintaining a high level at the 93rd percentile over the past three years[11] - Stock-type ETFs experienced a significant net outflow of 381.3 billion CNY, placing it at the 1.9th percentile over the past three years[18] Group 2: Trading Congestion - The trading heat for the machinery sector increased by 29 percentage points to 86%, while the construction sector rose by 24 percentage points to 72%[52] - The insurance sector's trading heat increased by 13 percentage points to 28%, whereas the light industry, photovoltaic, and military industries saw declines of 18, 17, and 16 percentage points, respectively[52] Group 3: Investor Sentiment - The A-share market saw a decline after five consecutive weeks of increases, with a drop in overall search heat for A-shares on social media[65] - Retail investor net inflow in the A-share market was 134.9 billion CNY last week, maintaining a high level at the 76.4th percentile over the past five years[2]

Group 1: Liquidity and Fund Flow - The supply side of funds is expanding, with net inflows of leveraged funds remaining high, and the issuance of equity public funds returning to high levels, with 172 billion units newly established[6] - Southbound funds have maintained a weekly average net inflow of over 10 billion for ten consecutive weeks, with a cumulative net inflow of nearly 200 billion[6] - The net inflow of margin financing last week was approximately 446.1 billion, marking a 97% percentile over the past three years, and the total margin financing balance reached 1.93 trillion[13] Group 2: Trading Activity and Market Sentiment - The trading heat for the mechanical industry increased by 55 percentage points to 67%, while the banking sector decreased by 20 percentage points to 51%[2] - Retail investor net inflow in the A-share market reached 132.6 billion, an increase of 539.8 billion from the previous value, marking a new high since April this year[2] - The Shanghai Composite Index reached a year-to-date high of 3600 points on July 23, driving an increase in A-share search heat on platforms like Kuaishou and Douyin[2] Group 3: Sector Performance - The net inflow for the pharmaceutical sector was 48.5 billion, while the petrochemical sector saw a net outflow of 8.0 billion[22] - The net inflow for the non-ferrous metals sector was 45.4 billion, and the machinery sector recorded a net inflow of 38.7 billion[22] - The stock-type ETF experienced a net outflow of 60 billion, which is at the 20.5% percentile over the past three years[23]

Quantitative Models and Construction Methods 1. Model Name: Interest Rate Bond Expected Return Model - **Model Construction Idea**: This model decomposes the expected return of interest rate bonds into several components and uses Monte Carlo simulations to predict the expected return for bonds of any maturity over a one-year holding period [8] - **Model Construction Process**: The expected return of interest rate bonds is decomposed into the following components: - Coupon yield - Roll yield - Duration yield - Convexity yield The formula for the expected return is: $ R \approx r_{N} + roll~yield + Dur \cdot (-\Delta r) + \frac{1}{2} Cx \cdot \Delta r^{2} $ Where: - $ r_{N} $ represents the coupon yield - $ roll~yield $ represents the roll-down return - $ Dur $ represents the duration - $ \Delta r $ represents the change in interest rates - $ Cx $ represents the convexity Based on this, the "interest rate bond odds" is defined as: $ Interest~Rate~Bond~Odds = 10Y~Bond~Expected~Return - 1Y~Bond~Expected~Return $ As of July 18, the expected return difference between 10Y and 1Y bonds was -3.2%, indicating extremely low odds for 10Y bonds [8] 2. Model Name: Short-Term Momentum Model - **Model Construction Idea**: This model predicts the short-term (1-month) price movement of interest rate bonds based on three key characteristics of interest rate movements: mean reversion around the interest rate center, 1-month short-term momentum, and 12-month long-term momentum [14] - **Model Construction Process**: The formula for the short-term momentum model is: $ \Delta r_{t+1} = \beta_{1}(\mu - r_{t}) + \beta_{2}(r_{t} - r_{t-1}) + \beta_{3}(r_{t} - r_{t-12}) + \sigma \sqrt{r_{t}} \cdot \varepsilon $ Where: - $ \mu $ represents the interest rate center - $ r_{t} $ represents the current interest rate - $ r_{t-1} $ and $ r_{t-12} $ represent the interest rates 1 month and 12 months ago, respectively - $ \beta_{1}, \beta_{2}, \beta_{3} $ are coefficients - $ \sigma $ represents volatility - $ \varepsilon $ represents random noise The model suggests that the 10Y bond may face short-term downward pressure, and recommends defensive allocation to 1Y bonds [14] 3. Model Name: Trading Heat Monitoring Model - **Model Construction Idea**: This model uses turnover rate and transaction proportion to measure the trading heat of long-term bonds, identifying risks of overcrowded trading [17] - **Model Construction Process**: - Turnover rate = (Trading volume of bonds with maturity >10 years) / (Outstanding balance of bonds with maturity >10 years) - Transaction proportion = (Trading volume of bonds with maturity >10 years) / (Total trading volume of all bonds) Historical data shows that when these indicators exceed 2 standard deviations, the future 1-3 month returns of long-term bonds are negative. When they exceed 4 standard deviations, the risk of significant drawdowns increases [17][18] --- Model Backtesting Results 1. Interest Rate Bond Expected Return Model - **10Y-1Y Expected Return Difference**: -3.2% (as of July 18, 2025) [8] 2. Short-Term Momentum Model - **Annualized Return**: 6.6% - **Maximum Drawdown**: 2.3% - **Q1 Avoided Drawdown**: Approximately 2.2% [14] 3. Trading Heat Monitoring Model - **Turnover Rate**: 1.0 standard deviation - **Transaction Proportion**: 2.2 standard deviations [18]

Liquidity and Fund Flow - Leverage funds continue to see net inflows, reaching a new high since late February, with net inflow of 268 billion CNY last week, placing it in the 90th percentile over the past three years[13] - Southbound funds maintained an average weekly net inflow exceeding 10 billion CNY for nine consecutive weeks, totaling nearly 1700 billion CNY[6] - IPO financing surged to 181.7 billion CNY, representing the 71st percentile over the past three years[26] Trading Congestion - The trading heat for the photovoltaic sector increased by 32 percentage points to 71%, while real estate rose by 27 percentage points to 60%[56] - The building materials sector saw a 25 percentage point increase to 66%, indicating heightened trading activity[56] - Conversely, the chemical sector decreased by 13 percentage points to 59%, and media fell by 9 percentage points to 58%[56] Investor Sentiment - Retail investor net inflow decreased to 566 billion CNY, down 321 billion CNY from the previous value, placing it in the 13.7th percentile over the past five years[2] - The search interest for self-media platforms like Kuaishou and Douyin has declined from previous highs, indicating a cooling in market enthusiasm[69] - The trend of public funds clustering has weakened, with a shift towards value stocks, particularly in electronics, cyclical, and consumer sectors[2]

Liquidity - The net inflow of leveraged funds remains high, with a net inflow of 225 billion CNY in margin financing, placing it in the 87th percentile over the past three years[8] - Southbound funds have maintained a weekly average net inflow of over 10 billion CNY for the past two months, totaling nearly 150 billion CNY[7] - Stock-type ETFs have seen a turnaround with a net inflow of 3 million CNY, compared to a previous outflow of 236 billion CNY[21] Trading Congestion - The trading heat for the construction materials sector increased by 39 percentage points to 49%, while the photovoltaic sector rose by 32 percentage points to 54%[54] - The steel sector's trading heat increased by 25 percentage points to 51%, while the non-ferrous metals sector decreased by 8 percentage points to 23%[54] - The chemical sector's trading heat fell by 6 percentage points to 72%, and the media sector decreased by 6 percentage points to 64%[54] Investor Sentiment - Retail investors saw a net inflow of 887.1 billion CNY, an increase of 35.4 billion CNY from the previous value, placing it in the 40.3 percentile over the past five years[83] - The net inflow of financing funds was 225.3 billion CNY, up by 99.3 billion CNY from the previous week[2] - The market experienced fluctuations, with the Shanghai Composite Index retreating from a high on July 11, leading to increased search interest in self-media platforms like Kuaishou and Douyin[5]

Core Insights - The recent outperformance of small-cap stocks is attributed to a significant influx of retail investor capital compared to institutional investors, indicating a rapid recovery in market risk appetite since September 2024, despite a lag in fundamental improvements [1][11] - The overall return of large-cap styles will depend on the emergence of a fundamental turning point and the return of institutional capital, with potential catalysts being the confirmation of an upward trend in the AI industry cycle or unexpected macro policy enhancements [1][11] Group 1: Misconceptions about Small-Cap Outperformance - Misconception 1: Macro liquidity easing is beneficial for small-cap stocks. Historical data shows that small-cap performance is not solely determined by macro liquidity conditions, as both small and large-cap stocks have outperformed in various liquidity environments [2] - Misconception 2: The influx of quantitative private equity funds is driving small-cap outperformance. The actual scale of private equity fund inflows has not been as significant as perceived, and quantitative funds are more likely to act as "discoverers" of excess returns rather than creators [4] - Misconception 3: Trading congestion is an effective timing indicator for small-cap stocks. Historical trends indicate that high trading activity does not necessarily lead to a downturn in small-cap stocks, as they can continue to outperform even during periods of high trading volume [6] Group 2: Drivers of Small-Cap Performance - The current small-cap outperformance may be primarily driven by changes in the micro-funding structure, particularly the irrational trading behavior of retail investors entering the market [8] - In both Hong Kong and A-share markets, the correlation between retail investor inflows and small-cap index performance suggests that retail participation is a significant factor in the recent small-cap outperformance [9] - The switch between small and large-cap styles may require a turning point in economic trends, with historical patterns indicating that institutional capital tends to lead market shifts when macro policies or industry trends experience breakthroughs [11]