Quantitative Models and Factor Analysis Quantitative Models and Construction Methods Model 1: ETF Hot Trend Strategy - **Model Name**: ETF Hot Trend Strategy - **Model Construction Idea**: The strategy is based on selecting ETFs with the highest and lowest prices in an upward trend and further filtering them based on the steepness of the regression coefficients of the highest and lowest prices over the past 20 days[31] - **Model Construction Process**: 1. Select ETFs where both the highest and lowest prices are in an upward trend 2. Construct support and resistance factors based on the steepness of the regression coefficients of the highest and lowest prices over the past 20 days 3. Choose the top 10 ETFs with the highest turnover rate in the past 5 days relative to the past 20 days to construct a risk parity portfolio[31] - **Model Evaluation**: The strategy achieved a return of 61.41% since 2025, with an excess return of 38.22% compared to the CSI 300 Index[31] Model 2: ETF Three-Strategy Fusion - **Model Name**: ETF Three-Strategy Fusion - **Model Construction Idea**: The strategy combines three industry rotation strategies driven by quantitative fundamentals, quality low volatility, and distressed reversal to achieve factor and style complementarity and reduce the risk of a single strategy[34] - **Model Construction Process**: 1. Construct industry rotation strategies based on quantitative fundamentals, quality low volatility, and distressed reversal 2. Combine the three strategies in equal weights to select industries from different dimensions[34] - **Model Evaluation**: The strategy achieved a cumulative return of 12.24% from April 10, 2017, to January 30, 2026, with a Sharpe ratio of 0.74[39] Model 3: All-Weather Strategy - **Model Name**: All-Weather Strategy - **Model Construction Idea**: The strategy aims to achieve stable returns by avoiding the "prediction" dilemma through diversified risk. It follows three basic principles: asset selection, risk adjustment, and structural hedging[53] - **Model Construction Process**: 1. Select assets 2. Adjust risks 3. Perform structural hedging to achieve balanced allocation and smooth out volatility[53] - **Model Evaluation**: The high-volatility version achieved an annualized return of 11.8% with an average maximum drawdown of 3.6% and a Sharpe ratio of 2.3. The low-volatility version achieved an annualized return of 8.8% with an average maximum drawdown of 2.0% and a Sharpe ratio of 3.4[61] Model Backtesting Results ETF Hot Trend Strategy - **Return**: 61.41% since 2025[31] - **Excess Return**: 38.22% compared to CSI 300 Index[31] ETF Three-Strategy Fusion - **Cumulative Return**: 12.24% from April 10, 2017, to January 30, 2026[39] - **Sharpe Ratio**: 0.74[39] All-Weather Strategy - **High-Volatility Version**: - **Annualized Return**: 11.8%[61] - **Average Maximum Drawdown**: 3.6%[61] - **Sharpe Ratio**: 2.3[61] - **Low-Volatility Version**: - **Annualized Return**: 8.8%[61] - **Average Maximum Drawdown**: 2.0%[61] - **Sharpe Ratio**: 3.4[61] Quantitative Factors and Construction Methods Factor 1: Profitability Yield Factor - **Factor Name**: Profitability Yield Factor - **Factor Construction Idea**: Measures the profitability of stocks to identify high-profitability stocks[63] - **Factor Construction Process**: Calculate the profitability yield of stocks and select those with the highest profitability yield[63] - **Factor Evaluation**: Achieved a positive return of 3.24% this week, indicating that high-profitability stocks regained market favor[63] Factor 2: Value Factor - **Factor Name**: Value Factor - **Factor Construction Idea**: Measures the value of stocks to identify high-value stocks[63] - **Factor Construction Process**: Calculate the value of stocks and select those with the highest value[63] - **Factor Evaluation**: Achieved a positive return of 2.67% this week, reflecting that high-value stocks gained market attention[63] Factor 3: Leverage Factor - **Factor Name**: Leverage Factor - **Factor Construction Idea**: Measures the leverage of stocks to identify high-leverage stocks[63] - **Factor Construction Process**: Calculate the leverage of stocks and select those with the highest leverage[63] - **Factor Evaluation**: Achieved a positive return of 1.32% this week, indicating that high-leverage stocks gained market attention[63] Factor Backtesting Results Profitability Yield Factor - **Weekly Return**: 3.24%[63] Value Factor - **Weekly Return**: 2.67%[63] Leverage Factor - **Weekly Return**: 1.32%[63]

Core Viewpoint - The discussion of "Old Deng" and "Young Deng" has evolved into a new narrative in the investment community, reflecting a clash of investment styles and market cycles, with a focus on whether to adhere to value investing or embrace growth trends [1][3]. Group 1: Investment Styles - "Old Deng" refers to investors who prefer mature industry leaders and are less concerned with short-term fluctuations, while "Young Deng" investors chase emerging technologies and market trends [3]. - The performance gap between these investment styles has widened significantly in the current market environment, with "Young Deng" stocks like AI and semiconductor companies outperforming traditional sectors [3][4]. - Fund managers are increasingly recognizing the need to balance their investment strategies between maintaining a value-oriented approach and adapting to growth opportunities [4][10]. Group 2: Market Dynamics - The recent market has seen a stark divide, with some funds experiencing significant gains in technology sectors, while others focusing on traditional sectors face performance pressures [4][8]. - The ongoing debate highlights the importance of understanding market cycles and the potential for value recovery in traditional sectors like finance and real estate [8][9]. - Fund managers emphasize the need for a diversified investment approach, suggesting that maintaining a flexible strategy can help navigate market volatility [10][11]. Group 3: Future Outlook - There is a consensus among fund managers that the current technology cycle, particularly in AI and related fields, is expected to last for several years, presenting both opportunities and risks [6][8]. - The importance of a robust investment thesis based on verified profitability and growth potential is underscored, with caution advised against overly optimistic projections [6][7]. - The ability to adapt and expand one's investment capabilities is seen as crucial for long-term success in a rapidly changing market landscape [10][11].

Core Viewpoint - The discussion of "Old Deng" and "Young Deng" has evolved into a new narrative in the investment community, reflecting a clash of investment styles and market cycles, with a focus on whether to adhere to value investing or embrace growth trends [1][3]. Group 1: Investment Styles - "Old Deng" refers to investors favoring mature industry leaders with less focus on short-term volatility, while "Young Deng" represents those chasing emerging technologies and market trends [3][5]. - The performance gap between these investment styles has widened significantly in the current market environment, with "Young Deng" stocks, such as those in AI and robotics, outperforming traditional sectors like real estate and banking [3][4]. Group 2: Market Dynamics - The recent market has seen a stark divide, with some funds experiencing significant gains in technology sectors, while others, adhering to traditional value investing, have faced performance pressures [4][6]. - Fund managers are increasingly recognizing the need to balance their investment strategies between maintaining a focus on value and adapting to growth opportunities in emerging sectors [5][7]. Group 3: Future Outlook - The ongoing transformation in investment philosophies is tied to broader industry shifts and the evolution of investor demographics, indicating a potential long-term change in market dynamics [5][8]. - There is a consensus among fund managers that understanding the cyclical nature of markets and being adaptable in investment strategies will be crucial for future success [6][9].

Group 1 - The concept of "景气度" (economic prosperity) is crucial in the Chinese stock market, serving as a common code behind high-performing stocks and a "safety valve" for measuring current corporate performance growth [1] - The market landscape for the first half of 2025 reveals a significant performance gap between new growth forces and established leaders, highlighting a shift in consumer preferences and market dynamics [1] - The rise of new consumption trends, particularly among the post-2000 generation, is changing market dynamics, with a preference for lifestyle and emotional value over traditional investments like real estate [1] Group 2 - The previous bull market saw sectors like solar energy, lithium batteries, and electric vehicles undergo a dual cleansing of performance and valuation, with high penetration rates leading to significant declines in both areas [2] - The AI industry is emerging as a new growth driver, with companies like Cambrian witnessing a 43-fold increase in revenue, challenging established market leaders [2] - Fund managers are showing generational differences in performance, with newer managers excelling in AI and innovative pharmaceuticals, while veteran managers remain cautious [2] Group 3 - The stock market is characterized by constant changes, with investors either chasing high-prosperity new stars or adhering to traditional value investment strategies [5] - The performance of various companies varies significantly, with some like POP MART showing a 286% increase, while others like Vanke and Kweichow Moutai experiencing declines of -21% and -38% respectively [7]

Core Insights - Central Huijin has significantly increased its holdings in A-share ETFs, reaching a total of 1.29 trillion yuan, which accounts for 42% of the total A-share ETF market size [1] - The increase in ETF holdings is seen as a move to boost market confidence, with a notable rise in broad-based ETFs [1][4] - The market is currently characterized by institutional dominance, with a focus on quality leading companies rather than speculative small-cap stocks [10] ETF Holdings Overview - Central Huijin's holdings in broad-based ETFs amount to 1.28 trillion yuan, an increase of 236.3 billion yuan compared to the end of 2024 [1][3] - Industry ETFs held by Central Huijin total 4.64 billion yuan, with a slight increase of 450 million yuan from the end of 2024 [3] - Thematic ETFs held by Central Huijin are valued at 2.28 billion yuan, with a marginal increase of 80 million yuan [3] Index Holdings Breakdown - The largest holdings by Central Huijin are in the following indices: CSI 300 (829.9 billion yuan), SSE 50 (137.1 billion yuan), CSI 1000 (129.5 billion yuan), CSI 500 (99.5 billion yuan) [6] - Central Huijin holds over 50% of the shares in several ETFs, including CSI 1000, SSE 180, SSE 50, and CSI 300 [8] Market Sentiment and Strategy - The current market trend is driven by institutional investors, with a preference for investing in high-quality leading companies based on fundamental analysis [10] - The strategy reflects a cautious approach towards market sentiment, focusing on large-cap stocks that represent the best core leaders in the market [10]

- 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]

Core Viewpoint - The article emphasizes that while valuation is a crucial concept in equity investment, its direct impact on stock prices is inconsistent and influenced by various factors [2][6]. Valuation and Market Conditions - Valuation's influence on stock prices is unstable, as shown in a study by Everbright Securities, which analyzed the relationship between valuation and stock price movements across different industries from January 2013 to February 2025 [2]. - Market tolerance for valuation varies under different conditions, particularly in relation to earnings growth rates [4][5]. - High-growth scenarios (earnings growth above 30%) show minimal differences in returns between high and low valuation combinations, especially when growth exceeds 100% [5]. - Conversely, in low-growth scenarios, market tolerance for high valuations decreases, leading to better performance from lower valuation combinations [5]. Market Sentiment and Valuation Preferences - Market sentiment, represented by turnover rates, affects investor preferences for valuation. During bullish sentiment, investors favor high-valuation sectors, while in bearish conditions, they lean towards low-valuation sectors [5]. - The combination of market sentiment with valuation metrics significantly enhances the effectiveness of industry grouping based on PE ratios [5]. Complexity of Valuation - Valuation is important for providing a long-term perspective on investment levels, but the "reasonable valuation" at any given moment is subject to multiple influences [6]. - Acknowledging the complexity of valuation and maintaining a respectful attitude towards market dynamics is essential for assessing investment opportunities related to valuation fluctuations [6].