Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Model - **Model Construction Idea**: The model is used to monitor the critical points of trend changes in the micro-cap stock index by analyzing the distribution of stock price movements over a specific time window [5][39] - **Model Construction Process**: The diffusion index is calculated based on the relative price changes of constituent stocks over a retrospective or forward-looking window. For example, if the horizontal axis is 0.95 and the vertical axis is 15 days, the value of 0.31 indicates that if all constituent stocks drop by 5% after 5 days, the diffusion index value is 0.31. The model uses thresholds to signal trading actions: - **First Threshold Method (Left-Side Trading)**: Triggered a sell signal on May 8, 2025, when the index reached 0.9850 [43] - **Delayed Threshold Method (Right-Side Trading)**: Triggered a sell signal on May 15, 2025, at 0.8975 [47] - **Double Moving Average Method (Adaptive Trading)**: Triggered a buy signal on July 3, 2025 [48] - **Model Evaluation**: The model effectively identifies trend changes but may be influenced by the distribution of constituent stocks and their updates [39][40] 2. Model Name: Small-Cap Low-Volatility 50 Strategy - **Model Construction Idea**: This strategy selects 50 stocks with small market capitalization and low volatility from the micro-cap stock index, rebalancing every two weeks [7][36] - **Model Construction Process**: - Select stocks with the smallest market capitalization and lowest volatility from the micro-cap index - Rebalance the portfolio bi-weekly - Benchmark: Wind Micro-Cap Stock Index (8841431.WI) - Transaction cost: 0.3% on both sides [7][36] - **Model Evaluation**: The strategy demonstrates strong performance in 2025 but underperformed in 2024, indicating sensitivity to market conditions [7][36] --- Model Backtesting Results 1. Diffusion Index Model - **First Threshold Method**: Triggered sell signal at 0.9850 on May 8, 2025 [43] - **Delayed Threshold Method**: Triggered sell signal at 0.8975 on May 15, 2025 [47] - **Double Moving Average Method**: Triggered buy signal on July 3, 2025 [48] 2. Small-Cap Low-Volatility 50 Strategy - **2024 Return**: 7.07%, underperformed by -2.93% relative to the benchmark [7][36] - **2025 YTD Return**: 69.79%, underperformed by -1.88% relative to the benchmark [7][36] --- Quantitative Factors and Construction Methods 1. Factor Name: Unadjusted Stock Price Factor - **Factor Construction Idea**: Measures the rank IC of unadjusted stock prices within the micro-cap stock index [4][17] - **Factor Construction Process**: - Calculate the rank IC of unadjusted stock prices weekly - Compare with historical averages for evaluation [4][17] - **Factor Evaluation**: Demonstrated strong performance this week with a rank IC of 0.177, significantly above the historical average of -0.015 [4][17] 2. Factor Name: Beta Factor - **Factor Construction Idea**: Measures the systematic risk of stocks within the micro-cap stock index [4][17] - **Factor Construction Process**: - Calculate the beta of each stock relative to the market - Evaluate weekly rank IC and compare with historical averages [4][17] - **Factor Evaluation**: Performed well this week with a rank IC of 0.15, above the historical average of 0.006 [4][17] 3. Factor Name: Illiquidity Factor - **Factor Construction Idea**: Captures the illiquidity of stocks within the micro-cap stock index [4][17] - **Factor Construction Process**: - Measure illiquidity based on trading volume and price impact - Evaluate weekly rank IC and compare with historical averages [4][17] - **Factor Evaluation**: Strong performance this week with a rank IC of 0.143, above the historical average of 0.04 [4][17] 4. Factor Name: 10-Day Return Factor - **Factor Construction Idea**: Tracks the short-term momentum of stocks within the micro-cap stock index [4][17] - **Factor Construction Process**: - Calculate the 10-day return for each stock - Evaluate weekly rank IC and compare with historical averages [4][17] - **Factor Evaluation**: Positive performance this week with a rank IC of 0.105, above the historical average of -0.061 [4][17] 5. Factor Name: PE_TTM Reciprocal Factor - **Factor Construction Idea**: Measures valuation based on the reciprocal of the trailing twelve-month price-to-earnings ratio [4][17] - **Factor Construction Process**: - Calculate the reciprocal of PE_TTM for each stock - Evaluate weekly rank IC and compare with historical averages [4][17] - **Factor Evaluation**: Moderate performance this week with a rank IC of 0.041, above the historical average of 0.017 [4][17] --- Factor Backtesting Results Top 5 Factors by Weekly Rank IC 1. **Unadjusted Stock Price Factor**: Weekly rank IC = 0.177, Historical Average = -0.015 [4][17] 2. **Beta Factor**: Weekly rank IC = 0.15, Historical Average = 0.006 [4][17] 3. **Illiquidity Factor**: Weekly rank IC = 0.143, Historical Average = 0.04 [4][17] 4. **10-Day Return Factor**: Weekly rank IC = 0.105, Historical Average = -0.061 [4][17] 5. **PE_TTM Reciprocal Factor**: Weekly rank IC = 0.041, Historical Average = 0.017 [4][17] Bottom 5 Factors by Weekly Rank IC 1. **Turnover Factor**: Weekly rank IC = -0.189, Historical Average = -0.082 [4][17] 2. **Momentum Factor**: Weekly rank IC = -0.132, Historical Average = -0.005 [4][17] 3. **Residual Volatility Factor**: Weekly rank IC = -0.13, Historical Average = -0.04 [4][17] 4. **10-Day Free Float Turnover Factor**: Weekly rank IC = -0.12, Historical Average = -0.062 [4][17] 5. **Liquidity Factor**: Weekly rank IC = -0.118, Historical Average = -0.041 [4][17]

本周，大盘再创本轮行情的新高。不过，就在大家对行情寄予更高期望之时，上证指数却迎来了连 续两天的调整。周五收盘后，美国非农数据不及预期，导致美股大幅调整。 大盘已调整两天，外围市场又传来利空，下周还会延续调整吗？8月份，应该注意什么？今天，达 哥和牛博士就大家关心的问题进行讨论。 不过，对身处其中的人，情况则不同。在这两波回调中，当时不少人认为"牛没了"，尤其是出现了 日K线5连阴的时候。因此，对于本轮回调，我认为，可能会让一些人对牛市的信仰产生动摇。 牛博士：达哥，你好，又到了我们周末聊行情的时间。你在上周日说，从历史来看，在突破重要压 力位之前会有一波回调。本周大盘已经回调了两个交易日，这是否就是你说的回调一波的情况？美国非 农数据不及预期，导致美股大幅调整，这个消息是否会加剧A股的调整进程？对于8月份的行情，你又 是如何看待的？ 道达：美国7月非农新增就业人数骤降至7.3万人，创下最近9个月以来的最低纪录，而市场预期是 10.4万人。另外，5月和6月的非农新增就业人数被大幅下修，由原先的14.4万、14.7万分别修正为1.9 万、1.4万。经过此次修正，5月和6月的新增就业减少了25.8万。 这个消息出 ...

- The report does not contain any specific quantitative models or factors for analysis[1][2][3]

Core Insights - The financing net inflow for Lian Ce Technology reached 16.11 million yuan last week, ranking 464th in the market [1] - The company operates in various sectors including specialized equipment, Jiangsu region, specialized and innovative enterprises, margin trading, micro-trading stocks, Xiaomi and Huawei automotive, and new energy vehicles [1] Financing Data - Last week, the total financing amount was 52.04 million yuan, while the repayment amount was 35.93 million yuan [1] - Over the past 5 days, the main capital outflow was 1.50 million yuan, with a decline of 0.47% [1] - Over the past 10 days, the main capital outflow was 518,300 yuan, with a decline of 0.1% [1] Company Overview - Jiangsu Lian Ce Electromechanical Technology Co., Ltd. was established in 2002 and is located in Nantong City, primarily engaged in other manufacturing industries [1] - The registered capital of the company is 64.40 million yuan, with a paid-in capital of 64.03 million yuan [1] - The legal representative of the company is Zhao Aiguo [1] Investment and Intellectual Property - The company has invested in 13 enterprises and participated in 294 bidding projects [1] - In terms of intellectual property, the company holds 3 trademark registrations and 70 patents, along with 6 administrative licenses [1]

【导读】回顾周末大事，汇总十大券商最新研判 中国基金报记者 泰勒 1.美国黑天鹅！7月非农就业人数增加7.3万人，不及市场预期 美国7月非农就业人数增加7.3万人，预估为增加10.4万人，前值为增加14.7万人。数据创9 个月以来新低。 更令人担忧的是5月和6月新增就业合计下修25.8万（相当于2个月新增就业近乎归0，当然不 排除7月就业继续下修的可能）。数据公布后，市场对美国经济下行的担忧演绎到了极致，美 元立刻跳水，几乎消化了7月底以来的一半涨幅，美股大跌，而9月降息概率也从此前的不降 息飙升至70%以上。 2.消息人士称主要产油国计划9月继续增产 8月3日，据央视新闻报道，据路透社援引消息人士的话报道，沙特、俄罗斯、伊拉克和阿联 酋等欧佩克和非欧佩克产油国中的 八个主要产油国 ，计划在8月3日举行的会议上批准9月 再 次大幅增产，日均增产54.8万桶 。 欧佩克和非欧佩克产油国中的8个主要产油国2023年11月宣布日均220万桶的自愿减产措 施，此后减产措施多次延期，于2024年12月延长至2025年3月底。8国今年3月决定自4月1 日起逐步增加石油产量，以回撤自愿减产措施。之后，这些主要产油国7月日均 ...

Quantitative Models and Construction Methods - **Model Name**: Diffusion Index Model **Construction Idea**: The model monitors the future critical points of diffusion index changes to predict market trends[40][41] **Construction Process**: 1. Define the horizontal axis as the relative price change of stocks in the index, ranging from +10% to -10% 2. Define the vertical axis as the review period length (T days) or future period length (N days), where T ranges from 20 to 10 days, and N = 20 - T 3. Calculate the diffusion index value for each combination of horizontal and vertical axis values 4. Example: For N=5 days and T=15 days, if all stocks drop by 5%, the diffusion index value is 0.51[40] **Evaluation**: The model indicates that current trends are driven by leading stocks rather than bottom stock rotation, suggesting the weakening of reversal factors and strengthening of fundamental factors[41] - **Model Name**: First Threshold Method (Left-Side Trading) **Construction Idea**: This method triggers signals based on predefined threshold values[44] **Construction Process**: 1. Monitor the diffusion index value daily 2. Trigger a signal when the index reaches a specific threshold 3. Example: On May 8, 2025, the diffusion index value of 0.9850 triggered a sell signal[44] **Evaluation**: Provides early warning signals for market reversals[44] - **Model Name**: Delayed Threshold Method (Right-Side Trading) **Construction Idea**: Similar to the first threshold method but with delayed signal generation[46][48] **Construction Process**: 1. Monitor the diffusion index value daily 2. Trigger a signal when the index reaches a delayed threshold 3. Example: On May 15, 2025, the diffusion index value of 0.8975 triggered a sell signal[48] **Evaluation**: Offers a more conservative approach compared to the first threshold method[48] - **Model Name**: Dual Moving Average Method (Adaptive Trading) **Construction Idea**: Uses moving averages to adapt to market trends[49] **Construction Process**: 1. Calculate short-term and long-term moving averages of the diffusion index 2. Generate buy or sell signals based on the crossover of these averages 3. Example: On July 3, 2025, the method issued a buy signal[49] **Evaluation**: Effective in capturing trend reversals during adaptive market conditions[49] Model Backtesting Results - **Diffusion Index Model**: Current value is 0.89, showing an increasing trend at the bottom level[40][41] - **First Threshold Method**: Triggered a sell signal at 0.9850 on May 8, 2025[44] - **Delayed Threshold Method**: Triggered a sell signal at 0.8975 on May 15, 2025[48] - **Dual Moving Average Method**: Triggered a buy signal on July 3, 2025[49] Quantitative Factors and Construction Methods - **Factor Name**: Illiquidity Factor **Construction Idea**: Measures the impact of stock liquidity on returns[4][35] **Construction Process**: 1. Rank stocks based on their liquidity metrics 2. Calculate the rank IC (information coefficient) for the factor 3. Example: Weekly rank IC is 0.268, historical average is 0.04[4][35] **Evaluation**: Strong performance in the current week, significantly above historical averages[4][35] - **Factor Name**: Single-Quarter Net Profit Growth Factor **Construction Idea**: Evaluates the growth rate of net profit over a single quarter[4][35] **Construction Process**: 1. Calculate the quarterly net profit growth rate for each stock 2. Rank stocks based on growth rates 3. Example: Weekly rank IC is 0.062, historical average is 0.02[4][35] **Evaluation**: Moderate performance, slightly above historical averages[4][35] - **Factor Name**: Unadjusted Stock Price Factor **Construction Idea**: Uses raw stock prices without adjustments for splits or dividends[4][35] **Construction Process**: 1. Rank stocks based on their unadjusted prices 2. Calculate the rank IC for the factor 3. Example: Weekly rank IC is 0.055, historical average is -0.016[4][35] **Evaluation**: Positive performance, reversing historical negative trends[4][35] - **Factor Name**: Dividend Yield Factor **Construction Idea**: Measures the dividend yield of stocks[4][35] **Construction Process**: 1. Calculate the dividend yield for each stock 2. Rank stocks based on yield values 3. Example: Weekly rank IC is 0.046, historical average is 0.021[4][35] **Evaluation**: Consistent performance, slightly above historical averages[4][35] - **Factor Name**: PB Reciprocal Factor **Construction Idea**: Uses the reciprocal of the price-to-book ratio[4][35] **Construction Process**: 1. Calculate the reciprocal of PB for each stock 2. Rank stocks based on reciprocal values 3. Example: Weekly rank IC is 0.042, historical average is 0.033[4][35] **Evaluation**: Stable performance, aligned with historical averages[4][35] Factor Backtesting Results - **Illiquidity Factor**: Weekly rank IC is 0.268, historical average is 0.04[4][35] - **Single-Quarter Net Profit Growth Factor**: Weekly rank IC is 0.062, historical average is 0.02[4][35] - **Unadjusted Stock Price Factor**: Weekly rank IC is 0.055, historical average is -0.016[4][35] - **Dividend Yield Factor**: Weekly rank IC is 0.046, historical average is 0.021[4][35] - **PB Reciprocal Factor**: Weekly rank IC is 0.042, historical average is 0.033[4][35]

Core Viewpoint - The current market sentiment is overly optimistic about reaching 8000 or even 10000 points, but the reality is that a bull market is driven by fundamentals, capital flow, and market sentiment, which require careful analysis rather than mere speculation [1] Market Conditions - **Trading Volume vs. Capital Intent**: The apparent high trading volume of over 1 trillion is misleading, as northbound capital has fluctuated five times in the past week, indicating a lack of genuine investment and more of a stock game among existing players [3] - **Profitability vs. Earnings Foundation**: While sectors like AI and robotics are experiencing significant gains, less than 30% of companies reported better-than-expected first-quarter results, suggesting that many firms are still recovering [3] - **Point Speculation vs. Historical Patterns**: Historically, A-shares have never experienced a bull market without a significant downturn first. The current index is only 10% away from previous highs, which does not indicate a "bottomed out" market [3] Challenges to Market Growth - **Economic Stability**: The recovery in consumer spending is weak, and capacity utilization rates are low, raising doubts about whether the fundamentals can support a rise to 10000 points [3] - **Incremental Capital**: Although total household deposits appear substantial, 90% of retail investors are heavily invested and hesitant to act, with new fund issuance only at one-third of the levels seen during the 2015 bull market, indicating a lack of fresh capital [3] - **External Risks**: Potential external shocks, such as tariffs from the U.S. and fluctuating Federal Reserve interest rate policies, pose significant risks to the A-share market [3] Investment Strategy - **Focus on High-Quality Companies**: Investors are advised to seek companies with high earnings certainty, strong policy barriers, and stable cash flows, rather than speculating on market points [4] - **Market Behavior Awareness**: A true bull market will experience volatility; a healthy market will recover from a 5% drop within three days, while prolonged declines should prompt investors to reduce their positions [4] Cautionary Notes - **Beware of "Bull Stock Traps"**: Recently hyped micro-cap stocks often have extremely high price-to-earnings ratios, and under the registration system, these stocks carry the highest risk of delisting [4]

Quantitative Models and Construction Methods Diffusion Index Model - **Model Name**: Diffusion Index Model - **Construction Idea**: The model monitors the relative performance of stocks within the micro-cap index over different time windows to identify potential turning points in market trends [41][42] - **Construction Process**: - The horizontal axis represents the percentage change in stock prices from +10% to -10% (1.1 to 0.9) - The vertical axis represents the length of the review window, ranging from 20 days to 10 days - For example, at horizontal axis 0.95 and vertical axis 15 days, the value of 0.37 indicates that if all stocks in the micro-cap index drop by 5% after 5 days, the diffusion index value is 0.37 - Formula: Diffusion Index = $\frac{\text{Number of stocks outperforming the benchmark}}{\text{Total number of stocks}}$ [41][42] - **Evaluation**: The model effectively identifies market trends but faces challenges when bottom-performing stocks are abandoned during strong upward trends [42] - **Testing Results**: Current diffusion index value is 0.94, indicating a strong upward trend [41][42] Threshold Methods - **Model Name**: Threshold Methods (First Threshold Method and Delayed Threshold Method) - **Construction Idea**: These methods use predefined thresholds to generate trading signals based on the diffusion index [45][49] - **Construction Process**: - First Threshold Method: Triggered a sell signal on May 8, 2025, when the diffusion index reached 0.9850 [45] - Delayed Threshold Method: Triggered a sell signal on May 15, 2025, when the diffusion index reached 0.8975 [49] - **Evaluation**: These methods provide clear trading signals but may lag during rapid market changes [45][49] - **Testing Results**: First Threshold Method value: 0.9850; Delayed Threshold Method value: 0.8975 [45][49] Dual Moving Average Method - **Model Name**: Dual Moving Average Method - **Construction Idea**: This method uses adaptive moving averages to generate trading signals based on market trends [50] - **Construction Process**: - The method compares short-term and long-term moving averages to identify buy or sell signals - On July 3, 2025, the method generated a buy signal [50] - **Evaluation**: The method adapts well to changing market conditions and provides timely signals [50] - **Testing Results**: Buy signal generated on July 3, 2025 [50] --- Quantitative Factors and Construction Methods Top Performing Factors - **Factor Names**: Non-liquidity factor, Unadjusted stock price factor, Beta factor, Standardized expected earnings factor, PE_TTM reciprocal factor [4][19][36] - **Construction Idea**: These factors are derived from stock characteristics and financial metrics to predict future returns [4][19][36] - **Construction Process**: - Non-liquidity factor: Measures the illiquidity of stocks - Unadjusted stock price factor: Uses raw stock prices without adjustments - Beta factor: Captures the sensitivity of stock returns to market movements - Standardized expected earnings factor: Standardizes analysts' earnings forecasts - PE_TTM reciprocal factor: Calculates the reciprocal of the trailing twelve-month price-to-earnings ratio - **Evaluation**: These factors show strong predictive power for stock returns [4][19][36] - **Testing Results**: - Non-liquidity factor IC: 0.353 (historical average: 0.04) - Unadjusted stock price factor IC: 0.348 (historical average: -0.016) - Beta factor IC: 0.247 (historical average: 0.005) - Standardized expected earnings factor IC: 0.141 (historical average: 0.014) - PE_TTM reciprocal factor IC: 0.092 (historical average: 0.017) [4][19][36] Underperforming Factors - **Factor Names**: Turnover factor, 10-day total market capitalization turnover rate factor, Liquidity factor, 10-day free float market capitalization turnover rate factor, Leverage factor [4][19][36] - **Construction Idea**: These factors are derived from trading activity and financial leverage metrics [4][19][36] - **Construction Process**: - Turnover factor: Measures trading volume relative to market capitalization - 10-day total market capitalization turnover rate factor: Calculates turnover rate over a 10-day window - Liquidity factor: Assesses the ease of trading stocks - 10-day free float market capitalization turnover rate factor: Similar to the total turnover rate but focuses on free float shares - Leverage factor: Measures financial leverage of companies - **Evaluation**: These factors exhibit weak predictive power and negative correlations with returns [4][19][36] - **Testing Results**: - Turnover factor IC: -0.336 (historical average: -0.082) - 10-day total market capitalization turnover rate factor IC: -0.286 (historical average: -0.06) - Liquidity factor IC: -0.278 (historical average: -0.041) - 10-day free float market capitalization turnover rate factor IC: -0.276 (historical average: -0.062) - Leverage factor IC: -0.225 (historical average: -0.006) [4][19][36] --- Strategy Performance Small-Cap Low-Volatility 50 Strategy - **Strategy Name**: Small-Cap Low-Volatility 50 Strategy - **Construction Idea**: Selects 50 stocks with small market capitalization and low volatility from the micro-cap index [7][19][37] - **Construction Process**: - Stocks are selected bi-weekly based on market capitalization and volatility criteria - Benchmark: Wind Micro-Cap Index (8841431.WI) - Transaction cost: 0.3% on both sides [7][19][37] - **Evaluation**: The strategy demonstrates strong performance but occasionally underperforms the benchmark [7][19][37] - **Testing Results**: - 2024 return: 7.07% (excess return: -2.93%) - 2025 YTD return: 62.07% (weekly excess return: -2.44%) [7][19][37]

Core Viewpoint - The A-share market is expected to experience a period of consolidation during the mid-year report disclosure phase, with a focus on defensive stocks with high earnings certainty, while also considering opportunities in AI, semiconductors, and state-owned enterprise reforms [1][15]. Market Performance - On July 14, the A-share market showed mild performance with the Shanghai Composite Index slightly up and the ChiNext Index slightly down, while trading volume decreased significantly to 1.48 trillion yuan [3]. - The market is currently in a phase of differentiation between large-cap and growth stocks, with main funds shifting from high-position thematic stocks to policy-driven sectors [3][12]. Sector Performance - The mechanical equipment, utilities, and home appliance sectors all saw gains exceeding 1%, driven by factors such as the acceleration of solid-state battery industrialization and increased engineering machinery exports [5][6]. - The real estate sector experienced a decline of 1.29%, reflecting market skepticism about the effectiveness of recent policy stimuli [8][7]. Investment Strategies - Companies are advised to adopt a balanced investment strategy, focusing on defensive sectors like banking and utilities for risk-averse investors, while higher-risk investors may consider technology growth sectors such as semiconductors and AI [15][12]. - The current market environment is characterized by a rotation of sectors, with opportunities across various industries, including those benefiting from policy support and industrial trends [12][15]. Earnings and Policy Impact - The mid-year earnings reports are expected to catalyze interest in sectors such as AI, military industry, and chemicals, with a focus on companies that exceed earnings expectations [12][15]. - The market is likely to remain active, with a structural market characteristic where individual stocks are performing well despite overall index fluctuations [11][15].

Group 1 - The core viewpoint of the articles indicates a significant divergence in stock performance, with high-position stocks continuing to underperform while the computing hardware sector shows substantial strength driven by strong earnings from key players like Xinyi Technology [1] - A total of 42 stocks hit the daily limit up, with 11 stocks in a continuous rise, and 7 of them achieving three consecutive limit ups, reflecting a晋级率 of 38.89% excluding ST and delisted stocks [1] - The overall market saw over 4000 stocks decline, with 16 stocks hitting the daily limit down, indicating a notable increase in downward pressure [1] Group 2 - In the computing hardware sector, major stocks with strong fundamentals performed exceptionally well, with Xinyi Technology hitting the limit up at 20%, and other stocks like Zhongji Xuchuang and Shenghong Technology rising over 10% [1] - Small-cap stocks showed relatively weaker performance, with the micro-cap stock index dropping over 2% during the trading session [1] - Specific stocks such as Liu Steel and Jinshi Technology have shown notable performance, with Liu Steel achieving 6 limit ups in 11 days and Jinshi Technology achieving 4 limit ups in 7 days, indicating strong market interest in these companies [2]