金融工程定期：开源交易行为因子绩效月报（2025年7月）-20250801

Quantitative Models and Construction Methods Barra Style Factors - Model Name: Barra Style Factors - Construction Idea: The Barra style factors are designed to capture the performance of different market styles, such as size, value, growth, and profitability, through specific factor definitions[4][14] - Construction Process: - Size Factor: Measures the market capitalization of stocks - Value Factor: Captures the book-to-market ratio of stocks - Growth Factor: Reflects the growth potential of stocks - Profitability Factor: Based on earnings expectations[4][14] - Evaluation: These factors are widely used in the industry to analyze market trends and style rotations[4][14] --- Open-source Trading Behavior Factors - Factor Name: Ideal Reversal Factor - Construction Idea: Identifies the strongest reversal days by analyzing the average transaction size of large trades[5][15] - Construction Process: 1. Retrieve the past 20 trading days' data for a stock 2. Calculate the average transaction size per day (transaction amount/number of transactions) 3. Identify the 10 days with the highest transaction sizes and sum their returns (M_high) 4. Identify the 10 days with the lowest transaction sizes and sum their returns (M_low) 5. Compute the factor as $M = M_{high} - M_{low}$[43] - Evaluation: Captures the microstructure of reversal forces in the A-share market[5][15] - Factor Name: Smart Money Factor - Construction Idea: Tracks institutional trading activity by analyzing minute-level price and volume data[5][15] - Construction Process: 1. Retrieve the past 10 days' minute-level data for a stock 2. Construct the indicator $S_t = |R_t| / V_t^{0.25}$, where $R_t$ is the return at minute $t$, and $V_t$ is the trading volume at minute $t$ 3. Sort minute-level data by $S_t$ in descending order and select the top 20% of minutes by cumulative trading volume 4. Calculate the volume-weighted average price (VWAP) for smart money trades ($VWAP_{smart}$) and all trades ($VWAP_{all}$) 5. Compute the factor as $Q = VWAP_{smart} / VWAP_{all}$[42][44] - Evaluation: Effectively identifies institutional trading patterns[5][15] - Factor Name: APM Factor - Construction Idea: Measures the difference in trading behavior between morning (or overnight) and afternoon sessions[5][15] - Construction Process: 1. Retrieve the past 20 days' data for a stock 2. Calculate daily overnight and afternoon returns for both the stock and the index 3. Perform a regression of stock returns on index returns to obtain residuals 4. Compute the difference between overnight and afternoon residuals for each day 5. Calculate the statistic $\mathrm{stat} = \frac{\mu(\delta_t)}{\sigma(\delta_t) / \sqrt{N}}$, where $\mu$ is the mean, $\sigma$ is the standard deviation, and $N$ is the sample size 6. Regress the statistic on momentum factors and use the residual as the APM factor[43][45][46] - Evaluation: Captures intraday trading behavior differences[5][15] - Factor Name: Ideal Amplitude Factor - Construction Idea: Measures the structural differences in amplitude information between high and low price states[5][15] - Construction Process: 1. Retrieve the past 20 trading days' data for a stock 2. Calculate the daily amplitude as $(\text{High Price}/\text{Low Price}) - 1$ 3. Compute the average amplitude for the top 25% of days with the highest closing prices ($V_{high}$) 4. Compute the average amplitude for the bottom 25% of days with the lowest closing prices ($V_{low}$) 5. Compute the factor as $V = V_{high} - V_{low}$[48] - Evaluation: Highlights amplitude differences across price states[5][15] - Factor Name: Composite Trading Behavior Factor - Construction Idea: Combines the above trading behavior factors using ICIR-based weights to enhance predictive power[31] - Construction Process: 1. Standardize and winsorize the individual factors within industries 2. Use the past 12 periods' ICIR values as weights to compute the composite factor[31] - Evaluation: Demonstrates superior performance in small-cap stock pools[32] --- Backtesting Results of Models and Factors Barra Style Factors - Size Factor: Return of 0.64% in July 2025[4][14] - Value Factor: Return of 0.59% in July 2025[4][14] - Growth Factor: Return of 0.16% in July 2025[4][14] - Profitability Factor: Return of -0.32% in July 2025[4][14] Open-source Trading Behavior Factors - Ideal Reversal Factor: - IC: -0.050 - RankIC: -0.061 - IR: 2.52 - Long-short monthly win rate: 78.3% (historical), 66.7% (last 12 months) - July 2025 long-short return: 0.47%[6][16] - Smart Money Factor: - IC: -0.037 - RankIC: -0.061 - IR: 2.76 - Long-short monthly win rate: 82.2% (historical), 91.7% (last 12 months) - July 2025 long-short return: 1.78%[6][19] - APM Factor: - IC: 0.029 - RankIC: 0.034 - IR: 2.30 - Long-short monthly win rate: 77.4% (historical), 58.3% (last 12 months) - July 2025 long-short return: 1.42%[6][23] - Ideal Amplitude Factor: - IC: -0.054 - RankIC: -0.073 - IR: 3.03 - Long-short monthly win rate: 83.6% (historical), 75.0% (last 12 months) - July 2025 long-short return: 3.86%[6][28] - Composite Trading Behavior Factor: - IC: 0.067 - RankIC: 0.092 - IR: 3.30 - Long-short monthly win rate: 82.6% (historical), 83.3% (last 12 months) - July 2025 long-short return: 2.13%[6][31]