Group 1 - The small-cap stocks have regained upward momentum, with the CSI 2000 Enhanced ETF (159552) increasing by 0.18% as of 9:55 AM, and showing a year-to-date increase of nearly 30% [1] - The CSI 2000 Enhanced ETF has seen a cumulative increase of 29.47% this year, with a significant inflow of funds and a continuous growth in scale for 10 consecutive days, resulting in a year-to-date scale growth of 722.42% [1] - From a calendar effect perspective, the average excess returns of various factors in July from 2015 to 2024 indicate that stocks with low valuation, low volatility, high profitability stability, and high dividend yield tend to perform well [1] Group 2 - The momentum factor shows an average monthly return of only 0.22% in July, with a win rate of 50%, suggesting that trend-following strategies are not favored during this month historically [1] - Overall, the advantageous factors in July exhibit significant defensive characteristics, and focusing on small-cap styles while selecting stocks with stable profit growth and high dividends may yield both beta and alpha returns [1]

Group 1: Market Overview - The national futures market in China has maintained a double-digit growth in trading volume and value in the first half of the year, with a total trading volume of 40.76 billion contracts and a total trading value of 339.73 trillion yuan, representing year-on-year increases of 17.82% and 20.68% respectively [3][4] - Gold futures continue to dominate the commodity futures market, with a trading value of 44.34 billion yuan in the first half of the year, surpassing last year's total trading value of 41.49 billion yuan, reflecting a year-on-year increase of 149% [4][5] Group 2: Gold Market Performance - The trading volume of gold options surged from 28.86 billion yuan in the first half of last year to 1017.87 billion yuan in the same period this year, marking a year-on-year increase of 252.64% [4][5] - The overall trading value of precious metals, including gold and silver, accounted for 17.61% of the national market [3][4] Group 3: Financial Futures - In the financial futures sector, the trading volume of the CSI 1000 index futures increased by 70.51% year-on-year, with a total trading value of 34.06 trillion yuan in the first half of the year [7][8] - The CSI 1000 index futures are seen as a representative of small-cap stocks, reflecting market preference for small-cap styles, as evidenced by the performance of the CSI 1000 index, which rose by 6.69% year-to-date [8]

Group 1 - The report indicates a positive outlook for equity assets, supported by a stock-bond rotation model showing a marginal decline in private sector financing growth but still in an upward trend, with inflation factors decreasing and economic recovery signals persisting [4][9] - The sentiment index for the A-share market has turned optimistic for the upcoming month, with indicators such as stock investment ratios and net inflows from large orders maintaining a bullish outlook [4][9] - The report recommends maintaining a high allocation to equity assets, with a focus on small-cap and growth styles for July, while suggesting stable fixed-income products for conservative investors [4][10] Group 2 - The report highlights the implementation of consumption policies aimed at enhancing consumer capacity and expanding financial support for consumption, with 19 key measures proposed [5][12] - A high-quality development plan for inclusive finance has been published, emphasizing the establishment of a comprehensive inclusive financial system over the next five years [5][12] - The second quarter monetary policy meeting indicated a more optimistic view of the domestic economy, while maintaining a stance of "moderate easing" in monetary policy [5][12] Group 3 - The report notes that the ETF market has performed well recently, with significant inflows into broad-based ETFs, particularly in the ChiNext index ETF and financial real estate sector ETFs [6][15] - The report mentions that 16 new ETFs were launched in the past two weeks, with a total issuance of 6.621 billion units, indicating growth in the ETF market [6][15] - The performance of thematic ETFs, such as those tracking AI and robotics, has been highlighted, with notable inflows and returns [6][17] Group 4 - The report discusses the wind power sector, forecasting a doubling of global offshore wind installations by 2025, with a compound annual growth rate of 21% expected over the next decade [19][20] - It also mentions the competitive landscape in the energy storage market, with prices for lithium iron phosphate battery systems continuing to decline, reflecting increased competition [20][21] - Investment recommendations include focusing on companies in the offshore wind sector and those involved in energy storage, highlighting specific firms such as Mingyang Smart Energy and Sunshine Power [21][22] Group 5 - The report emphasizes innovation in the liquor industry, with companies like Luzhou Laojiao focusing on low-alcohol and youth-oriented products to meet changing consumer demands [22][23] - It identifies opportunities in the beverage and snack sectors, driven by evolving consumer preferences and the introduction of functional products [22][23]

- The report tracks multiple quantitative factors across different markets, including equity market factors, commodity market factors, options market factors, and convertible bond market factors[7] Quantitative Factors and Construction Equity Market Factors - **Factor Name**: Market Style Factors - **Construction Idea**: Tracks the dominance of large-cap vs. small-cap and value vs. growth styles in the market[11][13] - **Construction Process**: - Large-cap vs. small-cap style: Evaluates the relative performance of large-cap stocks compared to small-cap stocks - Value vs. growth style: Assesses the relative performance of value-oriented stocks compared to growth-oriented stocks - Volatility metrics: Tracks the fluctuation in style dominance over time[11][13] - **Evaluation**: The market style is currently skewed towards large-cap and value stocks, with reduced volatility in style dominance[13] - **Factor Name**: Market Structure Factors - **Construction Idea**: Measures the dispersion and rotation within industry indices and stock concentration in trading[11][13] - **Construction Process**: - Industry index excess return dispersion: Tracks the spread of returns across different industry indices - Industry rotation speed: Measures the rate at which industries gain or lose prominence - Stock concentration: Evaluates the trading concentration of the top 100 stocks and the top 5 industries[11][13] - **Evaluation**: Industry return dispersion is at a one-year low, while industry rotation speed has increased. Stock concentration remains stable at low levels[13] - **Factor Name**: Market Activity Factors - **Construction Idea**: Tracks overall market volatility and turnover rates[12][13] - **Construction Process**: - Index volatility: Measures the fluctuation in market indices - Index turnover rate: Tracks the frequency of stock trading within indices[12][13] - **Evaluation**: Market volatility is at a one-year low, while turnover rates have slightly increased[13] Commodity Market Factors - **Factor Name**: Commodity Futures Factors - **Construction Idea**: Tracks trends, volatility, and liquidity across commodity sectors[28][31] - **Construction Process**: - Trend strength: Measures the directional movement in sectors like black metals, precious metals, and agricultural products - Volatility: Tracks the fluctuation in commodity prices - Liquidity: Assesses the ease of trading in different commodity sectors - Basis momentum: Evaluates the change in the basis (difference between spot and futures prices) for sectors like precious metals and non-ferrous metals[28][31] - **Evaluation**: Precious metals and non-ferrous metals show declining basis momentum, while agricultural products exhibit stronger trends. Liquidity in the energy sector is at a one-year high[31] Options Market Factors - **Factor Name**: Implied Volatility and Skewness - **Construction Idea**: Tracks implied volatility levels and skewness in options markets[36] - **Construction Process**: - Implied volatility: Measures the market's expectation of future volatility for indices like SSE 50 and CSI 1000 - Skewness: Evaluates the asymmetry in the distribution of returns, particularly for put options[36] - **Evaluation**: CSI 1000 implied volatility remains at historically low levels, and skewness for put options has increased, indicating reduced concerns over small-cap risks[36] Convertible Bond Market Factors - **Factor Name**: Convertible Bond Valuation Factors - **Construction Idea**: Tracks valuation metrics and trading activity in the convertible bond market[38] - **Construction Process**: - Premium rate: Measures the difference between the bond price and its conversion value - Trading activity: Tracks the turnover and liquidity in the convertible bond market - Credit spread: Evaluates the difference in yields between convertible bonds and risk-free bonds[38] - **Evaluation**: Premium rates have risen to near-May peaks, while low-premium bonds have decreased in proportion. Credit spreads have slightly narrowed[38] Backtesting Results Equity Market Factors - **Market Style Factors**: - Large-cap dominance observed - Value style outperformed growth style - Style volatility reduced to a one-year low[13] - **Market Structure Factors**: - Industry return dispersion at a one-year low - Increased industry rotation speed - Stable stock concentration at low levels[13] - **Market Activity Factors**: - Volatility at a one-year low - Slight increase in turnover rates[13] Commodity Market Factors - **Commodity Futures Factors**: - Decline in trend strength for black and precious metals - Increase in agricultural product trends - Energy sector liquidity at a one-year high - Decline in basis momentum for precious and non-ferrous metals[31] Options Market Factors - **Implied Volatility and Skewness**: - CSI 1000 implied volatility at historical lows - Increased skewness for put options, indicating reduced small-cap risk concerns[36] Convertible Bond Market Factors - **Convertible Bond Valuation Factors**: - Premium rates near May peaks - Decrease in low-premium bonds - Slight narrowing of credit spreads[38]

Market Overview - The A-share market is currently lacking catalysts, leading to increased volatility pressure. The downward space for large-cap stocks is relatively limited under the support of the Central Huijin Investment. Short-term focus is recommended on defensive sectors such as banks and low-volatility dividend stocks [2][4] - New consumption and innovative pharmaceuticals are facing higher adjustment risks in the short term, suggesting that investors should wait for risk release before seeking more cost-effective investment opportunities [2][4] Stock Market Factors - The large-cap value style remains dominant in the market, while the volatility of both large and small-cap styles has decreased. The volatility of value and growth styles is at a near-year low [6][8] - The excess return dispersion of industry indices is at a near-year low, with a decrease in the proportion of rising constituent stocks and an increase in industry rotation speed [6][8] - Market activity remains low, with the market volatility at a near-year low and a slight increase in turnover rate [7][8] Commodity Market Factors - In the commodity market, the trend strength of black and precious metals has decreased, while the trend strength of agricultural products has increased. The basis momentum of precious metals and non-ferrous metals has rapidly declined [19][22] - The volatility of energy and precious metals has slightly increased, while other sectors remain at near-year low volatility levels. Liquidity performance is mixed across sectors, with the energy sector at a near-year high in liquidity [19][22] Options Market Factors - The implied volatility levels of the SSE 50 and CSI 1000 show no significant trend, with the implied volatility of CSI 1000 remaining at historically low levels. The skewness of put options for CSI 1000 has increased, indicating a temporary alleviation of market concerns regarding small-cap stocks [28] Convertible Bond Market Factors - In the convertible bond market, valuations continue to rise, with the premium rate for bonds converting at 100 yuan increasing and approaching the peak seen in May. The proportion of bonds with low conversion premiums has significantly decreased, while market transaction volume remains stable within a fluctuating range [31]

Group 1 - The market sentiment score has further declined, indicating a bearish outlook as of June 20, with a score of 0.05, down from 0.8 the previous week [1][4][6] - The price-volume consistency has decreased, reflecting a lack of capital activity and increased divergence in market sentiment [4][6] - The overall trading volume in the A-share market has significantly decreased, with a daily trading volume of 1.09 trillion RMB, marking the lowest for the month [9] Group 2 - The electronic industry shows a significant upward trend, with a short-term trend score increase of 25.00%, indicating strong performance [18][19] - The banking, oil and petrochemical, communication, comprehensive, and national defense industries are identified as the top five sectors with the strongest short-term trends [18] - The small-cap value style is currently favored, while there are signs of a potential strengthening of the large-cap style [20]

Quantitative Models and Construction Methods 1. Model Name: Annualized Discount Model for CSI 500 Futures - **Model Construction Idea**: The model identifies optimal entry points for building positions based on historical performance when the annualized discount of CSI 500 futures exceeds a certain threshold, indicating market pessimism. [1][11] - **Model Construction Process**: - The model uses the annualized discount rate of the next-month contract of CSI 500 index futures as the key metric. - Historical data from 2017 onwards is analyzed to determine the relationship between the discount rate and subsequent returns. - Key findings: - When the annualized discount exceeds 15%, holding the index for more than 12 trading days results in average cumulative returns trending upward. - Holding for over 33 trading days yields a probability of positive cumulative returns exceeding 50%. - Holding for over 50 trading days increases the probability of positive returns to approximately 60%. - Formula: $ \text{Annualized Discount} = \frac{\text{Spot Price} - \text{Futures Price}}{\text{Futures Price}} \times \frac{365}{\text{Days to Maturity}} $ - Spot Price: Current index level - Futures Price: Price of the futures contract - Days to Maturity: Remaining days until the futures contract expires [11] - **Model Evaluation**: The model effectively captures market pessimism and identifies potential rebound opportunities, making it a useful tool for timing market entry. [11] --- Model Backtesting Results 1. Annualized Discount Model for CSI 500 Futures - **Key Metrics**: - Holding for 12 trading days: Average cumulative returns trend upward. - Holding for 33 trading days: Positive return probability > 50%. - Holding for 50 trading days: Positive return probability ~60%. [1][11] --- Quantitative Factors and Construction Methods 1. Factor Name: Proprietary Active Trader Activity Indicator - **Factor Construction Idea**: This factor measures the activity level of speculative funds (e.g., proprietary traders) to gauge market sentiment and risk appetite. [3][13] - **Factor Construction Process**: - Data Source: Derived from "Dragon and Tiger List" (龙虎榜) data. - The indicator tracks the marginal changes in active trader participation over time. - Observations: - From late April, the indicator showed a consistent decline, reflecting reduced risk appetite and cautious market sentiment. - Recently, the indicator has shown marginal improvement, suggesting a potential rebound in risk appetite. [3][13] - **Factor Evaluation**: The factor provides timely insights into the behavior of speculative funds, which can serve as a leading indicator for shifts in market sentiment. [3][13] 2. Factor Name: BARRA Style Factors - **Factor Construction Idea**: These factors assess the performance of various style attributes (e.g., momentum, volatility, size) to understand market preferences. [23][24] - **Factor Construction Process**: - Data Source: BARRA factor model. - Key Observations for the Week: - Fundamental factors (e.g., profitability) showed significant positive excess returns. - Stocks with high short-term momentum and high volatility outperformed. - Size-related factors (e.g., market capitalization) continued to underperform, indicating a preference for mid- to small-cap stocks. - Formula: Factor returns are calculated as the weighted average of stock returns within each style category. [23][24] - **Factor Evaluation**: The factors effectively capture shifts in market preferences, providing actionable insights for portfolio adjustments. [23][24] --- Factor Backtesting Results 1. Proprietary Active Trader Activity Indicator - **Key Metrics**: - Indicator showed consistent decline from late April, reflecting reduced risk appetite. - Recent marginal improvement suggests a potential rebound in speculative activity. [3][13] 2. BARRA Style Factors - **Key Metrics**: - Momentum: +0.2% weekly return. - Volatility: +0.2% weekly return. - Profitability: +0.3% weekly return. - Size: -0.5% weekly return. - Nonlinear Size: -0.3% weekly return. [23][24]

Summary of Conference Call Records Industry or Company Involved - Focus on the small-cap stock market and investment strategies within the A-share market Core Points and Arguments 1. **Small-Cap Stock Performance**: In May, small-cap stocks outperformed with an absolute return of over 2 percentage points, confirming the accuracy of the model's predictions. The outlook for June leans further towards small-cap stocks due to macroeconomic factors, market sentiment, and market conditions [1][3][4] 2. **Asset Allocation Views**: The current stance is optimistic towards domestic commodity assets, neutral to optimistic on stock assets, and cautious on bonds. The macro expectation model indicates a cautious view on stocks, neutral on bonds, and optimistic on commodities [5][6] 3. **Industry Rotation Model**: The industry rotation model shows rapid market rotation, with a focus on liquidity, momentum, and research information. In May, the portfolio included banking, home appliances, comprehensive finance, non-ferrous metals, electronic science and technology chips, and steel, achieving a total return of 3.7%, outperforming the benchmark by 0.7% [7][8] 4. **Recommended Industries for June**: The recommended sectors for June include comprehensive services, consumer services, telecommunications, agriculture, forestry, animal husbandry, fishing, steel, and electronics. The comprehensive sector has a high liquidity score, while agriculture and steel have advantages in research information [7][8] 5. **Active Quantitative Stock Selection Strategy**: The small-cap stock selection strategy performed best in May, with a focus on growth and small-cap strategies. The low attention stock selection strategy yielded a return of 9.6%, while the new stock selection strategy returned 7.5% [2][10] 6. **Investment Recommendations for June**: The analysis suggests focusing on dividend and small-cap selection strategies due to their improved cost-effectiveness compared to growth strategies [11] Other Important but Possibly Overlooked Content 1. **Market Sentiment Indicators**: Indicators such as Tianhong Fund's fundraising amount, the proportion of stocks hitting new highs, and the options PCR are all favorable for small-cap stocks [3][4] 2. **Risks to Monitor**: Potential risks include policy changes, sentiment fluctuations, and crowded institutional holdings that could impact small-cap stock performance [4] 3. **Quantitative Models Performance**: The quantitative models developed by the team have shown varying degrees of success, with the reinforcement learning factor extraction model maintaining an 11% cumulative return, outperforming the benchmark by 3.5 percentage points [11][12]

- The report focuses on the performance of Smart Beta portfolios, specifically Value, Growth, and Small-cap styles, constructed based on high beta elasticity and long-term stable excess returns objectives[7][8][10] - Value Smart Beta portfolios include "Value 50 Portfolio" and "Value Balanced 50 Portfolio", with weekly returns of 1.13% and 0.32%, respectively, and annual returns of 5.80% and 1.55%[4][8][10] - Growth Smart Beta portfolios include "Growth 50 Portfolio" and "Growth Balanced 50 Portfolio", with weekly returns of 1.27% and 1.59%, respectively, and annual returns of 0.86% and 6.05%[4][8][16] - Small-cap Smart Beta portfolios include "Small-cap 50 Portfolio" and "Small-cap Balanced 50 Portfolio", with weekly returns of 1.39% and 1.49%, respectively, and annual returns of 8.87% and 10.70%[4][8][22] - Performance metrics for Smart Beta portfolios include absolute returns, excess returns relative to benchmarks, and maximum relative drawdowns, with detailed data provided for each portfolio[8][10][22]

Group 1: Small Cap and Value Style Rotation Strategy - The latest quantitative model signals indicate a shift towards small-cap style for May, with historical data suggesting small-cap style is likely to outperform in this month [1] - The current market capitalization factor valuation spread is at 1.05, which is relatively low compared to historical highs of 1.7 to 2.6, indicating potential for small-cap outperformance [1] - Year-to-date, the small-cap style rotation strategy has achieved an excess return of 2.94% relative to an equal-weighted benchmark (CSI 300 and CSI 2000) [1] Group 2: Value and Growth Style Rotation Strategy - The latest quantitative model signals continue to favor value style for May, with expectations for value style to maintain its advantage [2] - Year-to-date, the value-growth style rotation strategy has generated an excess return of 4.6% compared to an equal-weighted benchmark (National Growth and National Value) [2] Group 3: Factor Performance Tracking - Among eight major factors, momentum and growth factors showed high positive returns in April, while liquidity and volatility factors exhibited high negative returns [2] - Year-to-date, momentum, analyst sentiment, and earnings volatility factors have shown positive returns, whereas industry momentum, liquidity, and short-term reversal factors have shown negative returns [2]