8月22日，阿拉丁盘中上涨2.08%，截至10:54，报15.67元/股，成交6911.93万元，换手率1.34%，总市值 52.12亿元。 资金流向方面，主力资金净流出457.08万元，特大单买入0.00元，占比0.00%，卖出244.22万元，占比 3.53%；大单买入1164.49万元，占比16.85%，卖出1377.35万元，占比19.93%。 资料显示，上海阿拉丁生化科技股份有限公司位于上海市浦东新区新金桥路36号南塔16楼，成立日期 2009年3月16日，上市日期2020年10月26日，公司主营业务涉及试剂的研发、生产及销售。主营业务收 入构成为：高端化学42.21%，生命科学32.73%，分析色谱13.78%，材料科学7.55%，实验耗材2.01%， 其他(补充)1.72%。 阿拉丁今年以来股价涨38.27%，近5个交易日涨1.16%，近20日涨5.88%，近60日涨25.28%。 分红方面，阿拉丁A股上市后累计派现2.41亿元。近三年，累计派现1.50亿元。 机构持仓方面，截止2025年3月31日，阿拉丁十大流通股东中，中欧医疗健康混合A（003095）位居第 三大流通股东，持股1357.71 ...

- The report does not contain any quantitative models or factors for analysis

- Model Name: ETF Premium and Discount Rate Model; Model Construction Idea: The model calculates the premium and discount rates of ETFs to reflect investor sentiment; Model Construction Process: The premium and discount rates are calculated using the formula: $ \text{Discount Rate} = \frac{\text{Total Transaction Amount of Block Trade}}{\text{Total Market Value of Shares Traded on the Day}} - 1 $ [23][26][27] - Model Name: Margin Trading Balance Model; Model Construction Idea: The model measures the balance of margin trading to reflect market activity; Model Construction Process: The balance of margin trading is calculated by summing the financing balance and the securities lending balance. The proportion of margin trading balance to the market's total circulating market value and the proportion of margin trading transactions to the market's total transaction amount are also calculated [19][22][24] - Model Name: Stock Index Futures Basis Model; Model Construction Idea: The model calculates the annualized basis rate of stock index futures to reflect market expectations; Model Construction Process: The annualized basis rate is calculated using the formula: $ \text{Annualized Basis Rate} = \frac{\text{Basis}}{\text{Index Price}} \times \left( \frac{250}{\text{Remaining Trading Days of the Contract}} \right) $ [28][29][31] - Factor Name: Sealing Rate; Factor Construction Idea: The factor measures the proportion of stocks that hit the highest price and closed at the highest price; Factor Construction Process: The sealing rate is calculated using the formula: $ \text{Sealing Rate} = \frac{\text{Number of Stocks with Highest Price and Closed at Highest Price}}{\text{Number of Stocks with Highest Price}} $ [16] - Factor Name: Consecutive Sealing Rate; Factor Construction Idea: The factor measures the proportion of stocks that closed at the highest price for two consecutive days; Factor Construction Process: The consecutive sealing rate is calculated using the formula: $ \text{Consecutive Sealing Rate} = \frac{\text{Number of Stocks Closed at Highest Price for Two Consecutive Days}}{\text{Number of Stocks Closed at Highest Price Yesterday}} $ [16] Model Backtest Results - ETF Premium and Discount Rate Model, Premium Rate: 1.77% (New Energy Vehicle Battery ETF), Discount Rate: 0.95% (CSI 2000 ETF) [23][25] - Margin Trading Balance Model, Margin Trading Balance: 19847 billion yuan, Financing Balance: 19706 billion yuan, Securities Lending Balance: 142 billion yuan, Margin Trading Balance to Circulating Market Value Ratio: 2.3%, Margin Trading Transactions to Market Transaction Amount Ratio: 10.4% [19][21][22] - Stock Index Futures Basis Model, Annualized Basis Rate: 0.25% (SSE 50), -3.17% (CSI 300), -11.41% (CSI 500), -12.84% (CSI 1000) [28][29][31] Factor Backtest Results - Sealing Rate, 59% [16] - Consecutive Sealing Rate, 25% [16]

The provided content does not contain any specific quantitative models or factors, nor does it include their construction processes, formulas, evaluations, or backtesting results. The documents primarily discuss market performance, sector and concept index movements, market sentiment, capital flows, ETF premiums/discounts, block trading discounts, and institutional activities. These are general market observations and statistics rather than detailed quantitative models or factor analyses.

The provided content does not contain any specific quantitative models or factors, nor does it include their construction processes, formulas, evaluations, or backtesting results. The document primarily focuses on market performance, sector analysis, market sentiment, capital flows, ETF premiums/discounts, block trading, and institutional activities. These are descriptive analyses and statistics rather than quantitative models or factor-based methodologies. If you have another document or specific quantitative content, please provide it for analysis