Quantitative Models and Construction Methods 1. Model Name: DTW Timing Model - **Model Construction Idea**: The model is based on a similarity approach, examining the similarity between current index trends and historical trends. It selects historical segments with high similarity as references and calculates the weighted average future returns and standard deviations of these segments to generate trading signals[26][28]. - **Model Construction Process**: 1. Use the DTW (Dynamic Time Warping) distance algorithm instead of Euclidean distance to measure similarity, as DTW can better handle time series misalignment issues[28]. 2. Select historical market segments with high similarity to the current market trend. 3. Calculate the weighted average future returns and standard deviations of the selected historical segments, where the weights are the inverse of the DTW distance. 4. Generate trading signals based on the average future returns and standard deviations[26]. 5. The model incorporates improved DTW algorithms, such as those with boundary constraints proposed by Sakoe-Chiba and Itakura, to address issues like "pathological matching" in traditional DTW algorithms[30]. - **Model Evaluation**: The DTW timing model is effective in general market conditions but may face challenges during periods of sudden macroeconomic policy changes, as observed in Q3 2023[17]. 2. Model Name: Foreign Capital Timing Model - **Model Construction Idea**: This model leverages information embedded in the price changes of two offshore assets related to A-shares: FTSE China A50 Index Futures (Singapore market) and the Southbound A50 ETF (Hong Kong market)[35]. - **Model Construction Process**: 1. Construct two indicators using FTSE China A50 Index Futures: basis and price divergence. 2. Combine these indicators to form the FTSE China A50 Index Futures timing signal. 3. Construct a price divergence indicator using the Southbound A50 ETF. 4. Combine the timing signals from the two assets to form the final foreign capital timing signal[35]. --- Model Backtesting Results 1. DTW Timing Model - **Absolute Return**: 38.56% since November 2022[17] - **Maximum Drawdown**: 21.32% since November 2022[17] - **2024 Performance on CSI 300**: - Absolute Return: 36.58% - Maximum Drawdown: 21.36% - Win Rate: 50.00% - Profit-Loss Ratio: 3.39[19] 2. Foreign Capital Timing Model - **Full Sample Performance (2014-2024)**: - Annualized Return: 18.96% (long-short), 14.19% (long-only) - Maximum Drawdown: 25.69% (long-short), 17.27% (long-only) - Daily Win Rate: ~55% - Profit-Loss Ratio: >2.5[21] - **2024 Performance (Out-of-Sample)**: - Absolute Return: 35.42% (long-only) - Maximum Drawdown: 8.23%[24] --- Quantitative Factors and Construction Methods No specific quantitative factors were explicitly mentioned in the report. --- Factor Backtesting Results No specific factor backtesting results were explicitly mentioned in the report.

Investment Rating - The report maintains an "Increase" rating for the financial products sector [1]. Core Insights - The report emphasizes the importance of structural changes in the market, indicating that a turning point in market trends may be approaching [5][17]. - The overall market performance for the week of July 7 to July 11, 2025, showed positive returns across most indices, but rapid rotation among stocks suggests a preference for holding rather than chasing hot stocks [17][20]. - The macro model for July scored -5, indicating a potential dominance of large-cap value stocks, while the overall market may experience adjustments [24]. - The technical timing model indicates a high risk level for the market, suggesting that while the trend remains positive, the relative position may be too high [17][21]. Summary by Sections A-share Market Overview (July 7 - July 11, 2025) - Major broad indices showed varied performance, with the top three being the Wind Micro-Pan Daily Equal Weight Index (2.99%), CSI 1000 (2.36%), and the ChiNext Index (2.36%) [10]. - Style indices also varied, with small-cap value (2.71%) and small-cap growth (2.31%) leading, while large-cap value (-0.18%) lagged [11]. - Among the Shenwan first-level industry indices, real estate (6.12%), steel (4.41%), and non-bank financials (3.96%) performed best, while coal (-1.08%) and banks (-1.00%) underperformed [15]. A-share Market Outlook (July 14 - July 18, 2025) - The report suggests a focus on structural changes, with a potential turning point in market trends [17]. - The macro model indicates that the market may experience adjustments, with a focus on performance post-earnings announcements [17][24]. - The report recommends a balanced ETF allocation strategy, anticipating a relatively volatile market with ongoing structural opportunities [65][66]. Fund Allocation Recommendations - The report advocates for a balanced ETF allocation strategy, emphasizing the importance of selecting funds with a minimum one-year establishment and a fund size exceeding 100 million [65][66].