- The report tracks the market trend by monitoring stocks that have reached new highs, using the 250-day high distance as a key metric[11][12] - The 250-day high distance is calculated as $ 1 - \frac{Closet}{ts\_max(Close, 250)} $ where Closet is the latest closing price and ts_max(Close, 250) is the maximum closing price over the past 250 trading days[11] - As of October 31, 2025, the 250-day high distances for major indices such as the Shanghai Composite Index, Shenzhen Component Index, and others are provided, with values ranging from 1.53% to 8.03%[12][13][15] Model and Factor Construction - **Model Name**: 250-day High Distance Model - **Construction Idea**: The model tracks the distance of the latest closing price from the highest closing price in the past 250 days to identify stocks that are reaching new highs[11] - **Construction Process**: - Calculate the 250-day high distance using the formula $ 1 - \frac{Closet}{ts\_max(Close, 250)} $ - Identify stocks with the smallest 250-day high distance, indicating they are at or near their 250-day high[11] - **Evaluation**: The model is effective in identifying stocks that are leading the market trend by reaching new highs[11] Factor Construction - **Factor Name**: Stable New High Stocks - **Construction Idea**: The factor aims to identify stocks that not only reach new highs but do so with stable price movements and strong momentum[26] - **Construction Process**: - Filter stocks that have reached a 250-day high in the past 20 trading days - Further filter based on analyst attention, relative strength, price stability, and trend continuation - Use metrics such as the sum of absolute daily returns over the past 120 days and the average 250-day high distance over the past 120 days to score and rank stocks[26][28] - **Evaluation**: This factor helps in identifying stocks with strong and stable upward trends, which are likely to continue performing well[26] Backtest Results - **250-day High Distance Model**: - Shanghai Composite Index: 1.53% - Shenzhen Component Index: 2.53% - CSI 300: 2.26% - CSI 500: 2.89% - CSI 1000: 1.85% - CSI 2000: 2.22% - ChiNext Index: 4.11% - STAR 50 Index: 8.03%[12][13][15] - **Stable New High Stocks Factor**: - Number of stocks reaching new highs in the past 20 days: 1077 - Highest number of new high stocks by industry: Electronics, Machinery, Basic Chemicals - Highest proportion of new high stocks by industry: Non-ferrous Metals, Coal, Steel - Highest number of new high stocks by index: CSI 2000, CSI 1000, CSI 500, CSI 300, ChiNext Index, STAR 50 Index[19][20][29]

- The report introduces a quantitative model named "250-day new high distance" to track market trends and identify hot spots. The model is based on momentum and trend-following strategies, emphasizing stocks that consistently hit new highs. The formula for calculating the 250-day new high distance is: $ 250\text{-day new high distance} = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ where $ Close_t $ represents the latest closing price, and $ ts\_max(Close, 250) $ is the maximum closing price over the past 250 trading days. If the latest closing price hits a new high, the distance equals 0; otherwise, it reflects the percentage drop from the peak [11][19][27] - The report evaluates the model positively, citing its ability to capture market leaders and trends effectively. It references studies by George (2004), William O'Neil, and Mark Minervini, which highlight the importance of tracking stocks near their 52-week highs for superior returns [11][18][21] - The model's backtesting results show that as of October 10, 2025, major indices such as the Shanghai Composite Index, Shenzhen Component Index, and others have respective 250-day new high distances of 0.94%, 2.70%, 1.97%, 2.00%, 1.49%, 2.61%, 4.55%, and 5.61%. Industry indices like power utilities, steel, and basic chemicals are closer to their 250-day highs, while sectors like food and beverage, banking, and transportation are farther away [12][13][31] - A factor named "Stable New High Stocks" is constructed to identify stocks with smooth price paths and consistent momentum. The factor considers analyst attention (minimum 5 buy/hold ratings in the past 3 months), relative price strength (top 20% in 250-day returns), price path smoothness (measured by price displacement ratio), and trend continuation (average 250-day new high distance over the past 120 days and past 5 days). The top 50 stocks meeting these criteria are selected [25][27][28] - The factor is positively evaluated for its focus on smooth momentum and its ability to identify stocks with strong and consistent performance. It references studies by Turan G Bali (2011) and Da Gurun (2012), which highlight the advantages of smooth price paths in momentum strategies [25][27][28] - Backtesting results for the "Stable New High Stocks" factor show that 50 stocks were selected, with the highest representation in cyclical and technology sectors. Examples include Industrial Internet, Xiangnong Chip, and Xingye Yinxi. The cyclical sector is dominated by basic chemicals, while the technology sector is led by electronics [28][30][32]

Quantitative Models and Construction Methods 1. Model Name: 250-Day New High Distance Model - **Model Construction Idea**: This model tracks the distance of stock prices or indices from their 250-day high to identify market trends and hotspots. It is based on the premise that stocks or indices near their recent highs tend to exhibit stronger momentum and potential for future gains[10][17]. - **Model Construction Process**: The 250-day new high distance is calculated as: $ 250\ Day\ New\ High\ Distance = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ Where: - $Close_t$ represents the latest closing price - $ts\_max(Close, 250)$ represents the maximum closing price over the past 250 trading days If the latest closing price reaches a new high, the distance is 0. If the price has fallen from the high, the distance is a positive value indicating the degree of decline[10]. - **Model Evaluation**: This model effectively captures momentum and trend-following characteristics, aligning with prior research on the predictive power of stocks near their 52-week highs[10][17]. 2. Model Name: Stable New High Stock Screening Model - **Model Construction Idea**: This model identifies stocks that exhibit stable momentum characteristics, focusing on smooth price paths and consistent new highs. It incorporates factors such as analyst attention, relative strength, and price stability to refine the selection process[23][25]. - **Model Construction Process**: The screening process involves the following steps: - **Analyst Attention**: Stocks must have at least 5 "Buy" or "Overweight" ratings in the past 3 months - **Relative Strength**: Stocks must rank in the top 20% of the market based on 250-day price performance - **Price Path Smoothness**: $ Price\ Path\ Smoothness = \frac{Absolute\ Price\ Change\ Over\ 120\ Days}{Sum\ of\ Daily\ Absolute\ Price\ Changes\ Over\ 120\ Days} $ Stocks with smoother price paths are prioritized - **New High Consistency**: The average 250-day new high distance over the past 120 days is calculated, and stocks with consistent proximity to new highs are selected - **Trend Continuation**: The average 250-day new high distance over the past 5 days is calculated, and the top 50 stocks are chosen based on this metric[23][25]. - **Model Evaluation**: This model emphasizes the temporal stability of momentum, leveraging smooth price paths and consistent trends to enhance predictive power[23][25]. --- Backtesting Results of Models 1. 250-Day New High Distance Model - **Indices' 250-Day New High Distance**: - Shanghai Composite Index: 3.97% - Shenzhen Component Index: 7.72% - CSI 300: 8.01% - CSI 500: 6.55% - CSI 1000: 5.20% - CSI 2000: 6.32% - ChiNext Index: 16.55% - STAR 50 Index: 8.64%[11][12][14] 2. Stable New High Stock Screening Model - **Selected Stocks**: 29 stocks were identified, including Wolong Electric, Newland, and Eilis. - **Sector Distribution**: - Manufacturing: 8 stocks (e.g., machinery) - Technology: 8 stocks (e.g., electronics) - Other sectors: Financials, healthcare, etc.[26][30][32] --- Quantitative Factors and Construction Methods 1. Factor Name: 250-Day New High Distance - **Factor Construction Idea**: This factor measures the relative position of a stock's price to its 250-day high, serving as a momentum indicator[10]. - **Factor Construction Process**: $ 250\ Day\ New\ High\ Distance = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ - $Close_t$: Latest closing price - $ts\_max(Close, 250)$: Maximum closing price over the past 250 trading days[10]. - **Factor Evaluation**: This factor is simple yet effective in capturing momentum trends, aligning with established research on the predictive power of stocks near their recent highs[10][17]. 2. Factor Name: Price Path Smoothness - **Factor Construction Idea**: This factor evaluates the stability of a stock's price movement over time, favoring stocks with smoother trajectories[23]. - **Factor Construction Process**: $ Price\ Path\ Smoothness = \frac{Absolute\ Price\ Change\ Over\ 120\ Days}{Sum\ of\ Daily\ Absolute\ Price\ Changes\ Over\ 120\ Days} $ Stocks with higher smoothness scores are prioritized[23]. - **Factor Evaluation**: This factor highlights the importance of temporal stability in momentum strategies, reducing noise from volatile price movements[23]. --- Backtesting Results of Factors 1. 250-Day New High Distance Factor - **Indices' 250-Day New High Distance**: - Shanghai Composite Index: 3.97% - Shenzhen Component Index: 7.72% - CSI 300: 8.01% - CSI 500: 6.55% - CSI 1000: 5.20% - CSI 2000: 6.32% - ChiNext Index: 16.55% - STAR 50 Index: 8.64%[11][12][14] 2. Price Path Smoothness Factor - **Selected Stocks**: 29 stocks were identified, including Wolong Electric, Newland, and Eilis. - **Sector Distribution**: - Manufacturing: 8 stocks (e.g., machinery) - Technology: 8 stocks (e.g., electronics) - Other sectors: Financials, healthcare, etc.[26][30][32]