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Quantitative Models and Construction - Model Name: Three-dimensional Timing Framework Construction Idea: The model integrates liquidity, divergence, and prosperity indicators to assess market timing and trends[7][12][14] Construction Process: 1. Liquidity indicator measures market liquidity trends[17] 2. Divergence indicator tracks market disagreement levels[16] 3. Prosperity indicator evaluates market sentiment and economic activity[19] 4. Combine these three dimensions into a unified framework to predict market movements[12][14] Evaluation: The model shows historical effectiveness in identifying market support levels and timing trends[7][14] - Model Name: ETF Hotspot Trend Strategy Construction Idea: Select ETFs based on price movement patterns and market attention to construct a risk-parity portfolio[25][26] Construction Process: 1. Identify ETFs with simultaneous upward trends in highest and lowest prices[25] 2. Calculate regression coefficients of price movements over the past 20 days to construct support-resistance factors[25] 3. Select top 10 ETFs with the highest turnover ratio (5-day/20-day) for portfolio construction[25] Evaluation: The strategy demonstrates cumulative excess returns over the CSI 300 index[26] - Model Name: Capital Flow Resonance Strategy Construction Idea: Combine financing and large-order capital flows to identify industries with strong capital resonance[29][33] Construction Process: 1. Define financing factor as the net financing buy minus net financing sell, neutralized by Barra market capitalization[33] 2. Define large-order factor as net inflow sorted by industry and neutralized by one-year trading volume[33] 3. Combine the two factors, excluding extreme industries and large financial sectors, to enhance strategy stability[33][36] Evaluation: The strategy achieves annualized excess returns of 13.5% since 2018, with an IR of 1.7[33] Model Backtesting Results - Three-dimensional Timing Framework: Historical performance indicates effective identification of market support levels and timing trends[14] - ETF Hotspot Trend Strategy: Cumulative excess return over CSI 300 index observed since the beginning of the year[26] - Capital Flow Resonance Strategy: - Annualized excess return: 13.5% since 2018 - IR: 1.7 - Weekly absolute return: 2.86% - Weekly excess return: 0.19%[33] Quantitative Factors and Construction - Factor Name: Beta Construction Idea: Measure stock sensitivity to market movements[39] Construction Process: Calculate stock beta using historical price data and market index movements[39] Evaluation: High-beta stocks outperform low-beta stocks, achieving 3.05% weekly return[39] - Factor Name: Momentum Construction Idea: Capture the continuation of stock price trends[39] Construction Process: Calculate momentum based on past price performance over a defined period[39] Evaluation: Momentum factor records 1.28% weekly return, indicating strong performance of previously high-performing stocks[39] - Factor Name: Liquidity Construction Idea: Assess market preference for high-liquidity stocks[39] Construction Process: Measure liquidity using trading volume and turnover ratios[39] Evaluation: Liquidity factor achieves 2.06% weekly return, reflecting market favorability for liquid stocks[39] - Factor Name: Illiquidity (Illia) Construction Idea: Evaluate stock price impact driven by large trading volumes[44][45] Construction Process: Measure daily price changes driven by trading volumes exceeding one billion[45] Evaluation: Illiquidity factor achieves 1.48% weekly excess return and 2.11% monthly excess return[45] - Factor Name: Volume Mean and Standard Deviation Construction Idea: Analyze trading volume trends over different time windows[44][45] Construction Process: 1. Calculate mean and standard deviation of trading volumes over 1-month, 3-month, 6-month, and 12-month windows[45] 2. Normalize and rank stocks based on these metrics[45] Evaluation: Volume-related factors show consistent positive excess returns across different time windows, with weekly returns ranging from 0.64% to 0.99%[45] - Factor Name: R&D Intensity Construction Idea: Measure the proportion of R&D expenditure relative to sales revenue[45] Construction Process: Calculate R&D expenses divided by total sales revenue[45] Evaluation: R&D intensity factor records 0.59% weekly excess return and 0.67% monthly excess return[45] Factor Backtesting Results - Beta Factor: Weekly return: 3.05%[39] - Momentum Factor: Weekly return: 1.28%[39] - Liquidity Factor: Weekly return: 2.06%[39] - Illiquidity Factor: Weekly excess return: 1.48%, Monthly excess return: 2.11%[45] - Volume Mean and Standard Deviation Factors: Weekly returns range from 0.64% to 0.99%, Monthly returns range from 1.49% to 2.29%[45] - R&D Intensity Factor: Weekly excess return: 0.59%, Monthly excess return: 0.67%[45]