Key Points - The article emphasizes a cautious approach in the short term, focusing on defensive sectors such as banks due to ongoing tariff negotiations and rising economic downward pressure [2][4] - It suggests that while small-cap growth stocks are currently favored, the overall market volatility is increasing, indicating potential risks if a turning point occurs [2][4] - The report highlights a decrease in the dispersion of excess returns among industry indices, with a slight decline in the proportion of rising constituent stocks and an increase in industry rotation speed [6][7] Market Overview - The market structure shows a stable concentration in the top 100 stocks, while the transaction share of the top five industries has slightly decreased [6][7] - Market activity has decreased, with a notable drop in the turnover rate of the Shanghai Stock Exchange 50 index, reaching its lowest level in nearly a year [6][7] Commodity Market Insights - In the commodity market, the strength of trends in precious metals and non-ferrous sectors has significantly increased, while energy and black metal sectors continue their trend [18][20] - The basis differential momentum for black and precious metals has rapidly increased, whereas it has decreased for energy and non-ferrous sectors [18][20] Options Market Analysis - The implied volatility levels for the Shanghai Stock Exchange 50 and the CSI 1000 show no significant trend, with the latter at historically low levels [23] - The skewness of the CSI 1000 put options has decreased, indicating a reduction in market concerns regarding small-cap stocks [23] Convertible Bond Market Overview - The convertible bond market remains stable in terms of valuation, with the premium rate for bonds convertible at 100 yuan and the pure debt premium rate showing steady trends [26] - The market turnover has improved, surpassing historical median levels, while credit spreads remain consistent with previous values [26]

1. Report Industry Investment Rating No information provided in the given report. 2. Core Views of the Report - The convertible bond market declined following the underlying stocks, and the valuation compressed on June 10, 2025 [1]. - The trading sentiment in the convertible bond market heated up, with the trading volume increasing [1]. - The market style favored large - cap value stocks [1]. 3. Summary by Relevant Catalogs Market Overview - Index Performance: The CSI Convertible Bond Index decreased by 0.28% compared to the previous day. The Shanghai Composite Index decreased by 0.44%, the Shenzhen Component Index decreased by 0.86%, the ChiNext Index decreased by 1.17%, the SSE 50 Index decreased by 0.39%, and the CSI 1000 Index decreased by 0.92% [1]. - Market Style: Large - cap value stocks were relatively dominant. Large - cap growth decreased by 0.71%, large - cap value decreased by 0.07%, mid - cap growth decreased by 0.70%, mid - cap value decreased by 0.09%, small - cap growth decreased by 1.01%, and small - cap value decreased by 0.34% [1]. - Capital Performance: The trading volume of the convertible bond market was 74.1 billion yuan, a 6.52% increase from the previous day. The total trading volume of the Wind All - A Index was 1.451437 trillion yuan, a 10.57% increase. The net out - flow of the main funds in the Shanghai and Shenzhen stock markets was 35.972 billion yuan, and the yield of the 10 - year treasury bond increased by 0.10bp to 1.66% [1]. Convertible Bond Price - The central price of convertible bonds decreased, and the proportion of high - price bonds decreased. The weighted average closing price of convertible bonds was 119.95 yuan, a 0.31% decrease from the previous day. The closing price of equity - biased convertible bonds was 162.79 yuan, a 0.01% increase; the closing price of bond - biased convertible bonds was 111.37 yuan, a 0.20% decrease; the closing price of balanced convertible bonds was 121.15 yuan, a 0.01% decrease [2]. - The proportion of bonds with a closing price above 130 yuan was 24.42%, a 2.34 - percentage - point decrease from the previous day. The most significant change in the proportion was in the range of 110 - 120 (including 120), with a proportion of 34.82%, a 1.06 - percentage - point increase. There were 8 bonds with a closing price below 100 yuan. The median price was 121.38 yuan, a 0.67% decrease from the previous day [2]. Convertible Bond Valuation - The valuation compressed. The conversion premium rate of the 100 - yuan par - value fitted convertible bonds was 23.00%, a 0.42 - percentage - point decrease from the previous day. The overall weighted par value was 89.91 yuan, a 0.64% decrease [2]. - The premium rate of equity - biased convertible bonds was 4.93%, a 0.91 - percentage - point decrease; the premium rate of bond - biased convertible bonds was 90.04%, a 0.53 - percentage - point increase; the premium rate of balanced convertible bonds was 19.78%, a 0.08 - percentage - point increase [2]. Industry Performance - In the A - share market, the top three industries with the largest declines were national defense and military industry (-1.97%), computer (-1.87%), and electronics (-1.65%); the top three industries with the largest increases were beauty care (+1.10%), banking (+0.48%), and medicine and biology (+0.33%) [3]. - In the convertible bond market, 24 industries declined. The top three industries with the largest declines were communication (-2.17%), computer (-1.58%), and building materials (-1.49%); the top three industries with the largest increases were beauty care (+0.82%), agriculture, forestry, animal husbandry and fishery (+0.34%), and banking (+0.32%) [3]. - For different sectors: - Closing price: The large - cycle sector decreased by 0.59%, the manufacturing sector decreased by 0.65%, the technology sector decreased by 1.44%, the large - consumption sector decreased by 0.31%, and the large - finance sector increased by 0.14% [3]. - Conversion premium rate: The large - cycle sector decreased by 0.4 percentage points, the manufacturing sector increased by 0.62 percentage points, the technology sector increased by 0.86 percentage points, the large - consumption sector increased by 0.87 percentage points, and the large - finance sector increased by 1.0 percentage point [3]. - Conversion value: The large - cycle sector decreased by 0.81%, the manufacturing sector decreased by 1.51%, the technology sector decreased by 1.82%, the large - consumption sector decreased by 0.08%, and the large - finance sector decreased by 0.68% [3]. - Pure - bond premium rate: The large - cycle sector decreased by 0.7 percentage points, the manufacturing sector decreased by 0.72 percentage points, the technology sector decreased by 2.0 percentage points, the large - consumption sector decreased by 0.43 percentage points, and the large - finance sector increased by 0.13 percentage points [4]. Industry Rotation - Beauty care, banking, and medicine and biology led the rise. For beauty care, the daily increase of the underlying stocks was 1.10%, and the convertible bonds increased by 0.82%; for banking, the daily increase of the underlying stocks was 0.48%, and the convertible bonds increased by 0.32%; for medicine and biology, the daily increase of the underlying stocks was 0.33%, and the convertible bonds increased by 0.18% [53].

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]

- The report primarily focuses on the weekly performance of the equity market, highlighting the resilience of the A-share market amidst global trade policy fluctuations and the rising prominence of technology and new consumption sectors [13][14][18] - It mentions the issuance of multiple quantitative products, including A500 Index Enhanced and Sci-Tech Composite Index Enhanced funds, which aim to enrich the market's product offerings [13][72][73] - The report tracks the weekly net inflow and outflow of funds across various ETF categories, showing significant movements in wide-base indices, industry-specific ETFs, and thematic ETFs [42][43][46] - Quantitative models such as the "Cinda Financial Engineering Industry Rotation Strategy" are referenced, which monitor marginal changes in holdings by high-performing funds to identify over-allocated and under-allocated sectors [37][38][41] - The report provides detailed fund flow data, including top-performing sectors like electronics, communication, and non-bank finance, as well as sectors with significant outflows such as automobiles, machinery, and pharmaceuticals [60][65][67]

- The report suggests that the market is currently at a good point for building positions due to sufficient pessimistic expectations indicated by factors such as futures discount and reduced trading volume[1][10][11] - The report highlights that if the annualized discount of the CSI 500 index futures exceeds 15%, buying the CSI 500 index and holding it for more than 12 trading days can lead to average cumulative returns increasing, with a win rate exceeding 50% after 33 trading days and reaching about 60% after 50 trading days[1][11] - The report mentions that the public funds are inclined to adjust their benchmark to the CSI 800, which has higher allocations in pharmaceuticals, chemicals, and computers compared to the previous mainstream benchmark CSI 300, potentially bringing event-driven returns[2][12] - The report constructs a "active capital activity indicator" based on the Dragon and Tiger list data, which has been declining since the end of April, indicating a decrease in risk appetite among active funds, but has recently shown signs of marginal recovery[3][13] - The report monitors the activity of informed traders, noting that the informed trader activity indicator has been hovering near the zero line, suggesting a cautious attitude towards the market[15] - The report calculates the rolling 12-month ROE and net profit growth rate changes for Shenwan first-level industries, with industries like light manufacturing, building materials, and real estate showing significant growth in net profit expectations[18][19] - The report observes that the net inflow of margin trading funds this week is highest in the pharmaceutical and biological industry, with a net inflow of 2.69 billion yuan[20][21] - The report analyzes the performance of BARRA style factors, noting that fundamental-related factors have shown significant positive excess returns, and funds prefer growth over value in the short term[23][24] Quantitative Models and Construction Methods 1. **Model Name: Active Capital Activity Indicator** - **Construction Idea**: Based on Dragon and Tiger list data to measure the activity level of active funds - **Construction Process**: The indicator is constructed by tracking the trading activity of active funds listed on the Dragon and Tiger list, with a focus on their buying and selling behavior over time[3][13] - **Evaluation**: Indicates the risk appetite of active funds, useful for understanding market sentiment[3][13] 2. **Model Name: Informed Trader Activity Indicator** - **Construction Idea**: Measures the activity level of informed traders to gauge market sentiment - **Construction Process**: The indicator is constructed by analyzing the trading activity of informed traders, focusing on their buying and selling patterns and their impact on market movements[15] - **Evaluation**: Provides insights into the cautious or optimistic attitudes of informed traders towards the market[15] Quantitative Factors and Construction Methods 1. **Factor Name: Futures Discount Factor** - **Construction Idea**: Based on the annualized discount of the CSI 500 index futures - **Construction Process**: The factor is constructed by calculating the annualized discount of the CSI 500 index futures and analyzing its impact on the index's performance over different holding periods[1][11] - **Evaluation**: Historical data shows that a significant discount can indicate a good entry point for building positions[1][11] 2. **Factor Name: Industry ROE and Net Profit Growth Factor** - **Construction Idea**: Based on the rolling 12-month ROE and net profit growth rate changes for Shenwan first-level industries - **Construction Process**: The factor is constructed by calculating the rolling 12-month ROE and net profit growth rate changes for each industry, and identifying industries with significant growth[18][19] - **Evaluation**: Helps identify industries with strong growth potential and positive market expectations[18][19] Factor Backtesting Results 1. **Futures Discount Factor** - **Win Rate after 33 Trading Days**: >50%[1][11] - **Win Rate after 50 Trading Days**: ~60%[1][11] 2. **Industry ROE and Net Profit Growth Factor** - **Light Manufacturing Net Profit Growth**: 0.63%[18][19] - **Building Materials Net Profit Growth**: 0.56%[18][19] - **Real Estate Net Profit Growth**: 0.49%[18][19] Style Factor Performance 1. **Turnover**: -0.3%[24] 2. **Financial Leverage**: 0.0%[24] 3. **Earnings Volatility**: 0.3%[24] 4. **Earnings Quality**: 0.2%[24] 5. **Profitability**: 0.3%[24] 6. **Investment Quality**: 0.1%[24] 7. **Long-term Reversal**: 0.1%[24] 8. **EP Value**: -0.1%[24] 9. **BP Value**: 0.0%[24] 10. **Growth**: 0.1%[24] 11. **Momentum**: 0.2%[24] 12. **Non-linear Size**: -0.3%[24] 13. **Size**: -0.5%[24] 14. **Volatility**: 0.2%[24] 15. **Near-term Reversal**: 0.4%[24] 16. **Dividend Yield**: -0.1%[24]

Investment Rating - The report suggests a positive outlook for the A-share market, indicating a potential for continued strong fluctuations and possible upward breakthroughs in the near term [3][6][14]. Core Insights - The report identifies that the end of the "filling pit" market phase is primarily driven by policies and external events, with historical data showing that out of seven instances since 2015, five resulted in market increases post-oscillation [6][14]. - Current short-term economic recovery trends are noted, with improvements in real estate sales and increased operational rates in the construction sector [19][24]. - The report emphasizes a focus on technology and new consumption sectors for investment, suggesting that these areas will continue to outperform in the near term [36][40]. Summary by Sections 1. Ending the Oscillation After the Filling Pit Market - The end of the oscillation phase is driven by policies and external events, with historical oscillation periods averaging 86 trading days, where five out of seven instances led to market increases [6][14]. - Key factors influencing the end of oscillation include policy easing and positive external events, such as geopolitical developments and economic agreements [6][14]. 2. Weekly Strategy: Continued Strong Oscillation in A-Shares - Short-term economic recovery is evident, with real estate sales showing resilience and construction project initiation rates improving [19][24]. - Liquidity remains loose, with significant reverse repos scheduled, indicating a strong willingness from the central bank to maintain liquidity [24][26]. 3. Industry Allocation: Focus on Technology and New Consumption - The report suggests that small-cap stocks may continue to outperform, as current market indicators are significantly below historical thresholds for style switching [33][34]. - Technology and new consumption sectors are highlighted as key areas for investment, with historical trends indicating these sectors perform well during oscillation periods [36][37]. - Valuation attractiveness is noted in sectors such as oil services, textiles, and media, with low PE ratios and high expected growth rates [40].

Group 1 - The A-share and Hong Kong stock markets are currently seen as having more opportunities than risks, with trading volume returning to 1.3 trillion [1] - The People's Bank of China will conduct a 1 trillion yuan reverse repurchase operation to maintain liquidity in the banking system, which is expected to lead to a rise in core assets and a revaluation of the market [3] - Large funds are anticipated to drive the Shanghai Composite Index above 3400 points, with expectations of a quick rally in key sectors such as liquor, pharmaceuticals, and financial real estate [5] Group 2 - The A-share market is expected to catch up with the significant rebound seen in the Hong Kong market, with predictions of increased trading volume potentially reaching 1.5 trillion or even 2 trillion [6] - The market is poised for a broad-based rally, with expectations that both large-cap and mid-cap stocks will rise, benefiting from the overall market sentiment [8]

Market Sentiment - Market sentiment has been fluctuating, with a three-day decline leading to complaints and a subsequent three-day rise causing excitement [1] - Investors are advised to manage their emotions and adhere to a trading system to capitalize on market movements [1] Market Trends - The A-share market saw a new account opening of 1.56 million in May, representing a year-on-year increase of 23%, although this is a significant decline from the peak in February and March, which saw a reduction of about 50% [2] - There is an expectation of a significant rebound in the market, particularly in sectors such as securities, real estate, liquor, and insurance, following a period of sharp declines [3][5] Sector Analysis - The banking and liquor sectors are showing unusual movements, indicating a potential intention to push the index towards 3,400 points [5] - The coal and electricity sectors are also anticipated to rebound, along with opportunities in oil and telecommunications [7] Investment Strategy - Investors are encouraged to avoid being overly clever in their trading strategies and to remain patient, as the market has not yet experienced a rapid upward movement this year [5][7] - The focus should be on industry rotation and maintaining a long-term perspective rather than reacting to short-term market fluctuations [7]

- The report introduces the **Industry Basic Tracking Model**, which monitors industry fundamentals and identifies the top-performing industries based on their sentiment and activity levels. The model highlights transportation, food & beverage, and coal as the industries with the highest sentiment, while media, communication, and banking show lower sentiment levels[3][8][9] - The **Crowding Factor** is introduced to measure the disparity between leading and lagging stocks within an industry across three dimensions: volatility, liquidity, and systemic risk. Higher crowding factors indicate elevated risks such as high volatility, active trading turnover, or increased beta exposure. For example, the food & beverage industry shows historically high crowding factors, while industries like agriculture, pharmaceuticals, machinery, consumer services, and coal exhibit historically low crowding factors[3][17][18] - The **Crowding Factor** is calculated using metrics such as stock volatility, liquidity, and beta exposure. It reflects the degree of market concentration and trading activity within an industry. Higher values suggest speculative trading and heightened systemic risk, while lower values indicate reduced market activity and risk exposure[17][18][28] - The pharmaceutical industry demonstrates a divergence between sentiment and crowding factors, with sentiment decreasing by 0.06 and crowding factors increasing by 0.28. This is attributed to short-term policy benefits, event-driven catalysts, and market sentiment, despite the lack of comprehensive recovery in industry fundamentals[12][15][17] - The report emphasizes that industries with high crowding factors, such as food & beverage, may face risks of speculative trading and systemic volatility. Conversely, industries with low crowding factors, such as agriculture, pharmaceuticals, machinery, consumer services, and coal, may present opportunities for stable investment due to reduced speculative activity[17][18][28]

Investment Insights - The report indicates an increase in the risk of "herding" behavior in the market, suggesting a cautious approach until the risk is released [3][4] - Current market focus remains on defensive sectors such as banking, pharmaceuticals, nuclear power, and new consumption themes, with a recommendation to wait for adjustment pressure to ease before making further investments [4] Stock Market Analysis - In the past week, small-cap growth stocks outperformed, while volatility in both large and small-cap styles increased, indicating instability in market styles [6] - The dispersion of excess returns among industry indices has decreased to a near one-year low, with a slight decline in the proportion of rising constituent stocks [6] - Market activity showed a slight increase in volatility, but turnover rates continued to decline, particularly in the Shanghai Stock Exchange 50, which reached historically low turnover levels [6] Commodity Market Overview - The commodity market displayed divergent trends, with energy and black metal sectors maintaining their momentum, while precious metals and non-ferrous metals showed upward trends [15] - The basis momentum for the black metal sector increased, while agricultural products remained at a low basis momentum [15] - Volatility was high in the energy sector, while other sectors experienced low-level fluctuations [15] Options Market Insights - Implied volatility for the Shanghai Stock Exchange 50 and CSI 1000 showed no significant trend before the Dragon Boat Festival, with long-term contracts experiencing a relative increase in implied volatility compared to short-term contracts [20] - The skew of put options relative to call options for the CSI 1000 maintained an advantage, with a noticeable increase in open interest, indicating market expectations of potential adjustments in small-cap stocks [20] Convertible Bond Market Trends - The convertible bond market saw a slight rebound, with the premium rate for bonds convertible at 100 yuan recovering, although the proportion of low-premium convertible bonds increased slightly [23] - Market transaction volume remained stable, and credit spreads significantly narrowed [23]