Quantitative Models and Construction Methods - **Model Name**: Style Rotation Model **Model Construction Idea**: The model is built from basic style factors such as valuation, market capitalization, volatility, and momentum. It incorporates a style timing and scoring system, leveraging micro-level features and machine learning techniques to optimize style selection and rotation[4][9]. **Model Construction Process**: 1. Start with 80 fundamental micro factors as raw features, categorized based on the proprietary multi-factor system of Dongwu Securities[9]. 2. Construct 640 micro-level features from these factors[4][9]. 3. Replace the absolute proportion division of style factors with commonly used indices as style stock pools, creating new style returns as labels[4][9]. 4. Use a rolling training process with a Random Forest model to avoid overfitting, select optimal features, and generate style recommendations[4][9]. 5. Combine style timing results and scoring outcomes to build a monthly frequency style rotation framework[4][9]. **Model Evaluation**: The model effectively integrates micro-level features and machine learning to enhance style rotation performance, mitigating overfitting risks[4][9]. Model Backtesting Results - **Style Rotation Model**: - Annualized Return: 16.52% - Annualized Volatility: 20.46% - IR: 0.81 - Monthly Win Rate: 57.01% - Maximum Drawdown: 25.68% - Excess Annualized Return (Hedged against Benchmark): 11.04% - Excess Annualized Volatility (Hedged against Benchmark): 11.08% - Excess IR (Hedged against Benchmark): 1.00 - Excess Monthly Win Rate (Hedged against Benchmark): 55.14% - Maximum Drawdown (Hedged against Benchmark): 9.00%[4][10][11]

证券之星消息，11月6日，央企ETF（159959）融资买入4.2万元，融资偿还2.91万元，融资净买入1.29万 元，融资余额60.98万元，近3个交易日已连续净买入累计8.79万元，近20个交易日中有12个交易日出现 融资净买入。 | 交易日 | 融资净买入(元) | | 融资余额(元) | 占流通市值比 | | --- | --- | --- | --- | --- | | 2025-11-06 | | 1.29万 | 60.98万 | | | 2025-11-05 | | 4.24万 | 59.70万 | | | 2025-11-04 | | 3.26万 | 55.46万 | | | 2025-11-03 | | -8.65万 | 52.19万 | | | 2025-10-31 | | -3.51万 | 60.85万 | | | 交易日 | 两融余额(元) | 余额变动(元) | 变动幅度 | | --- | --- | --- | --- | | 2025-11-06 | 60.98万 | 1.29万 | 2.15% | | 2025-11-05 | 59.70万 | 4.24万 | 7.64% | ...

Report Summary 1. Report Industry Investment Rating - Not provided in the given content 2. Core Viewpoints of the Report - The strategy is based on the research reports "Strategy Portfolio Report under Industry Rotation: Quantitative Analysis from the Perspective of Industry Style Continuity and Switching" (20241007) and "Research on the Overview and Allocation Methods of the Stock - type ETF Market: Taking the ETF Portfolio Based on the Industry Rotation Strategy as an Example" (20241013) to construct a strategy portfolio of industry and theme ETFs [2] - In the week of 20250811, the model recommends allocating sectors such as joint - stock banks, games, and semiconductors. In the next week, the strategy will newly hold products like Game ETF, Science and Technology Innovation Chip Design ETF, and Satellite ETF, and continue to hold products like Bank ETF, Financial Real Estate ETF, and Gold Stock ETF [2] - As of last weekend, some ETFs and the trading timing signals of the underlying indexes gave daily or weekly risk warnings [2] 3. Summary by Relevant Catalogs Performance Tracking - During the period from 20250804 to 20250808, the cumulative net return of the strategy was about 2.62%, and the excess return relative to the CSI 300 ETF was about 1.41% [3] - From October 14, 2024, to the present, the cumulative out - of - sample return of the strategy was about 7.08%, and the cumulative excess relative to the CSI 300 ETF was about - 0.79% [3] Future 1 - Week Recommended ETFs (20250811 - 20250815) | Fund Code | ETF Name | Holding Status | ETF Market Value (billion yuan) | Heavy - Positioned Shenwan II Industry and Weight | Weekly Timing Signal | Daily Timing Signal | | --- | --- | --- | --- | --- | --- | --- | | 512800 | Bank ETF | Continue to hold | 151.38 | Joint - stock banks (44.73%) | 1 | - 1 | | 159869 | Game ETF | Transfer in | 73.17 | Games (81.29%) | 1 | 1 | | 588780 | Science and Technology Innovation Chip Design ETF | Transfer in | 2.77 | Semiconductors (95.73%) | 1 | 1 | | 159940 | Financial Real Estate ETF | Continue to hold | 7.99 | Securities (29.12%) | 1 | - 1 | | 517520 | Gold Stock ETF | Continue to hold | 46.34 | Precious metals (41.51%) | 1 | 1 | | 510000 | Central Enterprise ETF | Continue to hold | 1.21 | State - owned large - scale banks (18.11%) | 1 | 1 | | 512690 | Wine ETF | Continue to hold | 152.39 | Baijiu (85.37%) | - 1 | - 1 | | 159206 | ZETF | Transfer in | 1.33 | Military electronics II (34.22%) | 1 | 1 | | 159786 | VRETF | Transfer in | 1.32 | Optoelectronics (26.64%) | 1 | 1 | | 159652 | Non - ferrous 50 ETF | Transfer in | 5.21 | Industrial metals (49.34%) | 1 | 1 | [9] Near 1 - Week ETF Holdings and Performance (20250804 - 20250808) | Fund Code | Current Holding Status | ETF Name | ETF Market Value (billion yuan) | Near 1 - Week Increase/Decrease (%) | | --- | --- | --- | --- | --- | | 562550 | - | Green Power ETF | 1.21 | 1.50 | | 512800 | Continue to hold | Bank ETF | 151.38 | 1.99 | | 512690 | Continue to hold | Wine ETF | 152.39 | 1.06 | | 159768 | - | Real Estate ETF | 6.13 | 2.14 | | 159940 | Continue to hold | Financial Real Estate ETF | 7.99 | 1.41 | | 515220 | Transfer out | Coal ETF | 80.20 | 3.78 | | 159996 | Transfer out | Home Appliance ETF | 12.72 | 2.55 | | 510060 | Continue to hold | Central Enterprise ETF | 1.21 | 1.42 | | 516550 | Transfer out | Agricultural ETF | 1.87 | 1.76 | | 517520 | Continue to hold | Gold Stock ETF | 46.34 | 8.91 | | - | ETF Portfolio Average Return | - | - | 2.62 | | 510300 | - | CSI 300 ETF | 3819.72 | 1.21 | | - | ETF Portfolio Excess Return | - | - | 1.41 | [10]