Quantitative Models and Construction Methods 1. Model Name: 250-Day New High Distance - **Model Construction Idea**: This model tracks the distance of a stock or index from its 250-day high to identify market trends and hotspots. It is based on the premise that stocks nearing their 52-week high tend to outperform, as supported by prior research (e.g., George@2004, William O'Neil's CANSLIM system, and Mark Minervini's "Stock Market Wizard").[11][18][21] - **Model Construction Process**: The 250-day new high distance is calculated as follows: $ 250 \text{ Day New High Distance} = 1 - \frac{\text{Close}_{t}}{\text{ts\_max(Close, 250)}} $ - $\text{Close}_{t}$: Latest closing price - $\text{ts\_max(Close, 250)}$: 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 positive, indicating the percentage drop.[11] - **Model Evaluation**: This model effectively identifies market leaders and trends, aligning with momentum and trend-following strategies.[11][18] 2. Model Name: Stable New High Stock Screening - **Model Construction Idea**: This model focuses on identifying stocks with stable momentum characteristics, emphasizing smooth price paths and consistent new highs. Research suggests that smoother momentum stocks outperform those with jumpy price paths (e.g., Bali et al., 2011; Da et al., 2012).[25][27] - **Model Construction Process**: Stocks are screened from the pool of those hitting 250-day highs in the past 20 trading days based on the following criteria: - **Analyst Attention**: At least 5 "Buy" or "Overweight" ratings in the past 3 months - **Relative Strength**: Top 20% in 250-day price performance - **Price Stability**: Evaluated using two metrics: - **Price Path Smoothness**: Ratio of price displacement to price path length - **New High Consistency**: Average 250-day new high distance over the past 120 days - **Trend Continuation**: Average 250-day new high distance over the past 5 days Stocks meeting these criteria are ranked, and the top 50% are selected.[25][27] - **Model Evaluation**: This model captures stocks with strong and stable momentum, leveraging underreaction to smooth price paths for enhanced returns.[25][27] --- Model Backtesting Results 1. 250-Day New High Distance - **Indices**: - Shanghai Composite: 0.00% - Shenzhen Component: 5.06% - CSI 300: 4.64% - CSI 500: 3.65% - CSI 1000: 0.91% - CSI 2000: 0.00% - ChiNext Index: 10.71% - STAR 50 Index: 10.59%[12][13][15] 2. Stable New High Stock Screening - **Selected Stocks**: 46 stocks, including Shenghong Technology, Borui Pharmaceutical, and Shijia Photon[28][33] - **Sector Distribution**: - Manufacturing: 14 stocks (e.g., machinery) - Technology: 13 stocks (e.g., computers)[28][33] --- Quantitative Factors and Construction Methods 1. Factor Name: 250-Day New High Distance - **Factor Construction Idea**: Measures the relative position of a stock's price to its 250-day high, serving as a momentum indicator.[11] - **Factor Construction Process**: $ 250 \text{ Day New High Distance} = 1 - \frac{\text{Close}_{t}}{\text{ts\_max(Close, 250)}} $ - $\text{Close}_{t}$: Latest closing price - $\text{ts\_max(Close, 250)}$: Maximum closing price over the past 250 trading days[11] - **Factor Evaluation**: Effectively identifies momentum leaders and market trends.[11][18] 2. Factor Name: Price Path Smoothness - **Factor Construction Idea**: Quantifies the smoothness of a stock's price trajectory, with smoother paths indicating stronger momentum.[25][27] - **Factor Construction Process**: $ \text{Price Path Smoothness} = \frac{\text{Price Displacement}}{\text{Price Path Length}} $ - **Price Displacement**: Net change in price over a period - **Price Path Length**: Sum of absolute daily price changes over the same period[27] - **Factor Evaluation**: Highlights stocks with stable momentum, leveraging underreaction to smooth price paths.[25][27] 3. Factor Name: New High Consistency - **Factor Construction Idea**: Measures the average proximity to 250-day highs over a specified period, indicating sustained momentum.[27] - **Factor Construction Process**: $ \text{New High Consistency} = \text{Mean(250 Day New High Distance over 120 Days)} $[27] - **Factor Evaluation**: Captures stocks with consistent momentum, emphasizing sustainability.[27] 4. Factor Name: Trend Continuation - **Factor Construction Idea**: Measures short-term proximity to 250-day highs, indicating recent momentum strength.[27] - **Factor Construction Process**: $ \text{Trend Continuation} = \text{Mean(250 Day New High Distance over 5 Days)} $[27] - **Factor Evaluation**: Identifies stocks with strong short-term momentum, complementing longer-term factors.[27] --- Factor Backtesting Results 1. 250-Day New High Distance - **Indices**: - Shanghai Composite: 0.00% - Shenzhen Component: 5.06% - CSI 300: 4.64% - CSI 500: 3.65% - CSI 1000: 0.91% - CSI 2000: 0.00% - ChiNext Index: 10.71% - STAR 50 Index: 10.59%[12][13][15] 2. Price Path Smoothness - **Selected Stocks**: 46 stocks, including Shenghong Technology, Borui Pharmaceutical, and Shijia Photon[28][33] 3. New High Consistency - **Selected Stocks**: 46 stocks, with top sectors being manufacturing (14 stocks) and technology (13 stocks)[28][33] 4. Trend Continuation - **Selected Stocks**: 46 stocks, with top sectors being manufacturing (14 stocks) and technology (13 stocks)[28][33]

Quantitative Models and Construction Methods 1. Model Name: 250-Day New High Distance Model - **Model Construction Idea**: This model tracks the distance of a stock's closing price from its 250-day high to identify market trends and hotspots. It is based on the premise that stocks nearing their 52-week highs tend to outperform, as highlighted in prior research by George (2004) and others[10][17]. - **Model Construction Process**: The formula for the 250-day new high distance is: $ 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; otherwise, the distance is positive, indicating the percentage drop from the high[10]. - **Model Evaluation**: This model effectively captures momentum and trend-following strategies, aligning with the principles of notable investors like William O'Neil and Mark Minervini[10][17]. 2. Model Name: Stable New High Stock Screening Model - **Model Construction Idea**: This model identifies stocks with stable price paths and consistent upward trends, leveraging the "smooth momentum" effect. Research suggests that stocks with smoother price paths yield higher returns than those with volatile paths[23]. - **Model Construction Process**: The screening criteria include: - **Price Path Smoothness**: Measured as the ratio of the absolute value of the past 120-day price change to the sum of absolute daily price changes over the same period[23]. - **Analyst Attention**: At least five "buy" or "overweight" ratings in the past three months[26]. - **Relative Strength**: The stock's 250-day return ranks in the top 20% of the market[26]. - **Trend Continuity**: The average 250-day new high distance over the past 120 days[26]. - **Trend Extension**: The average 250-day new high distance over the past five days, with the top 50 stocks selected[26]. - **Model Evaluation**: This model emphasizes the importance of smooth price trajectories and consistent momentum, which are less likely to attract excessive investor attention, thereby enhancing returns[23]. --- Model Backtesting Results 1. 250-Day New High Distance Model - **Key Indices' 250-Day New High Distance**: - Shanghai Composite Index: 0.50% - Shenzhen Component Index: 8.58% - CSI 300: 6.44% - CSI 500: 6.62% - CSI 1000: 4.53% - CSI 2000: 1.33% - ChiNext Index: 15.45% - STAR 50 Index: 12.60%[2][11][31] 2. Stable New High Stock Screening Model - **Selected Stocks**: 33 stocks were identified, including Shenghong Technology, Jingbeifang, and Giant Network[27][32]. - **Sector Distribution**: - Technology: 9 stocks (e.g., electronics) - Manufacturing: 8 stocks (e.g., machinery)[27][32] --- Quantitative Factors and Construction Methods 1. Factor Name: 250-Day New High Distance - **Factor Construction Idea**: Measures the relative position of a stock's closing price to its 250-day high, capturing momentum and trend-following characteristics[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 widely recognized for its ability to identify leading stocks and market trends, as supported by academic and practical research[10][17]. 2. Factor Name: Price Path Smoothness - **Factor Construction Idea**: Quantifies the smoothness of a stock's price trajectory, emphasizing consistent upward trends over volatile movements[23]. - **Factor Construction Process**: $ Price\ Path\ Smoothness = \frac{Absolute\ Value\ of\ 120\ Day\ Return}{Sum\ of\ Absolute\ Daily\ Returns\ over\ 120\ Days} $[23] - **Factor Evaluation**: This factor highlights stocks with stable momentum, which are less likely to be overreacted to by investors, leading to stronger performance[23]. --- Factor Backtesting Results 1. 250-Day New High Distance Factor - **Key Indices' 250-Day New High Distance**: - Shanghai Composite Index: 0.50% - Shenzhen Component Index: 8.58% - CSI 300: 6.44% - CSI 500: 6.62% - CSI 1000: 4.53% - CSI 2000: 1.33% - ChiNext Index: 15.45% - STAR 50 Index: 12.60%[2][11][31] 2. Price Path Smoothness Factor - **Selected Stocks**: 33 stocks were identified, including Shenghong Technology, Jingbeifang, and Giant Network[27][32]. - **Sector Distribution**: - Technology: 9 stocks (e.g., electronics) - Manufacturing: 8 stocks (e.g., machinery)[27][32]

Group 1 - The report tracks stocks, industries, and sectors that are reaching new highs, indicating market trends and hotspots [1][4] - As of June 6, 2025, the distance to the 250-day new high for major indices is as follows: Shanghai Composite Index at 2.99%, Shenzhen Component Index at 11.41%, CSI 300 at 8.98%, CSI 500 at 8.98%, CSI 1000 at 6.94%, CSI 2000 at 4.25%, ChiNext Index at 20.03%, and STAR Market 50 Index at 12.00% [5][21] - Among the CITIC first-level industry indices, banking, pharmaceuticals, light manufacturing, electricity and public utilities, and agriculture-related industries are closest to their 250-day new highs, while coal, oil and petrochemicals, real estate, food and beverage, and electric equipment and new energy industries are further away [8][21] Group 2 - A total of 777 stocks reached a 250-day new high in the past 20 trading days, with the highest number in the basic chemicals, machinery, and pharmaceuticals sectors [2][22] - The highest proportion of new high stocks is found in the banking, textile and apparel, and light manufacturing sectors, with respective proportions of 71.43%, 27.27%, and 24.24% [22][23] - The manufacturing and cyclical sectors had the most new high stocks this week, with 266 and 195 stocks respectively, while the technology, pharmaceuticals, consumer, and financial sectors had 106, 91, 73, and 43 stocks respectively [15][23] Group 3 - The report identifies 38 stable new high stocks, including Sanofi, Wancheng Group, and Shijia Photon, based on criteria such as analyst attention, relative strength, price path stability, and continuity of new highs [3][19] - The manufacturing sector had the most stable new high stocks, with 11, while the consumer sector had 8, with the mechanical industry leading in manufacturing and the food and beverage industry leading in consumption [19][23]

- The report introduces a quantitative model named "250-Day New High Distance" to track market trends and identify leading stocks. The model calculates the distance of the latest closing price from the highest closing price in the past 250 trading days using the formula: $ 250\text{-Day New High Distance} = 1 - \frac{\text{Closet}}{\text{ts\_max(Close, 250)}} $ where "Closet" represents the latest closing price, and "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; otherwise, it is a positive value indicating the degree of fallback [11][12][13] - The model is evaluated positively as it aligns with momentum and trend-following strategies, which have been proven effective in previous studies. It also references methodologies from notable investors like William O'Neil and Mark Minervini, emphasizing the importance of tracking stocks that consistently hit new highs [11][18] - The report provides backtesting results for major indices using the "250-Day New High Distance" model. As of May 23, 2025, the distances for key indices are: - Shanghai Composite Index: 4.05% - Shenzhen Component Index: 11.85% - CSI 300: 8.78% - CSI 500: 10.70% - CSI 1000: 9.41% - CSI 2000: 7.40% - ChiNext Index: 20.73% - STAR 50 Index: 12.98% [12][13][31] - Another quantitative factor introduced is "Stable New High Stocks," which focuses on stocks with smooth price paths and sustained momentum. The factor is constructed using criteria such as analyst attention, relative price strength, price path smoothness, and trend continuation. Specific metrics include: - Analyst attention: At least 5 buy or overweight ratings in the past 3 months - Relative price strength: Top 20% in market-wide 250-day returns - Price path smoothness: Evaluated using metrics like cumulative absolute returns over 120 days - Trend continuation: Average 250-day new high distance over the past 120 days and past 5 days [24][26][27] - 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 on the "boiling frog effect" and smooth price paths, which suggest that stocks with less extreme price movements tend to outperform [24][26] - Backtesting results for the "Stable New High Stocks" factor show that 41 stocks were selected based on the criteria. These stocks are distributed across sectors, with the manufacturing and consumer sectors having the highest representation (11 stocks each). Notable stocks include Wanchen Group, Sansheng Guojian, and Yanjin Shop [27][30][32]

Group 1: Market Trends and Highs - The report tracks stocks, industries, and sectors reaching new highs, serving as market indicators and highlighting the effectiveness of momentum and trend-following strategies [1][4] - As of May 23, 2025, the distance to the 250-day new high for major indices is as follows: Shanghai Composite Index 4.05%, Shenzhen Component Index 11.85%, CSI 300 8.78%, CSI 500 10.70%, CSI 1000 9.41%, CSI 2000 7.40%, ChiNext Index 20.73%, and STAR Market 12.98% [5][18] Group 2: New High Stocks Overview - A total of 647 stocks reached a 250-day new high in the past 20 trading days, with the highest numbers in the basic chemicals, machinery, and pharmaceuticals sectors, totaling 93, 88, and 53 stocks respectively [11][19] - The highest proportion of new high stocks is found in the banking, textile and apparel, and transportation sectors, with respective proportions of 64.29%, 24.24%, and 23.58% [11][19] Group 3: Stable New High Stocks - The report identifies 41 stable new high stocks, with the manufacturing and consumer sectors contributing the most, each with 11 stocks selected [16][19] - The automotive industry leads in the manufacturing sector for new highs, while the food and beverage industry leads in the consumer sector [16][19] Group 4: Sector and Concept Indexes - Among the sector indices, banking, automotive, home appliances, electric power and utilities, and non-ferrous metals are closest to their 250-day new highs, with distances of 0.96%, 2.38%, 3.08%, 1.95%, and 4.71% respectively [7][18] - Concept indices such as automotive, banking selection, gold, innovative drugs, and banking are also near their 250-day new highs [8][18]

- Model Name: 250-Day High Distance Model; Model Construction Idea: This model tracks the distance of the latest closing price from the highest closing price in the past 250 trading days to identify market trends and hot spots[11]; Model Construction Process: The formula used is $ 250 \text{ Day High Distance} = 1 - \frac{Closet}{ts\_max(Close, 250)} $ where Closet is the latest closing price and ts_max(Close, 250) is the maximum closing price in the past 250 trading days[11]; Model Evaluation: This model effectively captures market momentum and trend-following strategies[11] - Factor Name: Stable New High Stocks; Factor Construction Idea: This factor selects stocks that have recently hit new highs and exhibit stable price paths, considering analyst attention, relative strength, and trend continuation[24][26]; Factor Construction Process: The selection criteria include: - Analyst Attention: At least 5 buy or hold ratings in the past 3 months - Relative Strength: Top 20% in market performance over the past 250 days - Price Stability: Evaluated using the sum of absolute daily returns over the past 120 days and the smoothness of the price path - New High Continuity: Average 250-day high distance over the past 120 days - Trend Continuation: Average 250-day high distance over the past 5 days[24][26]; Factor Evaluation: This factor captures stocks with strong and stable momentum, potentially leading to higher returns[24][26] Model Backtest Results - 250-Day High Distance Model, Shanghai Composite Index: 4.23%[12] - 250-Day High Distance Model, Shenzhen Component Index: 9.82%[12] - 250-Day High Distance Model, CSI 300 Index: 9.27%[12] - 250-Day High Distance Model, CSI 500 Index: 7.66%[12] - 250-Day High Distance Model, CSI 1000 Index: 6.18%[12] - 250-Day High Distance Model, CSI 2000 Index: 7.34%[12] - 250-Day High Distance Model, ChiNext Index: 19.01%[12] - 250-Day High Distance Model, STAR 50 Index: 9.65%[12] Factor Backtest Results - Stable New High Stocks, Number of Stocks: 40[27] - Stable New High Stocks, Sector with Most Stocks: Cyclical (11 stocks), Financial (10 stocks)[27] - Stable New High Stocks, Top Sectors: Transportation in Cyclical, Banking in Financial[27]