“量价淘金”选股因子系列研究（十五）：高、低位放量事件簇：正负向信号的有机结合

Quantitative Models and Construction Methods 1. Model Name: Daily Frequency "High/Low Volume" Signal - Model Construction Idea: Define "high volume at high price" and "high volume at low price" events using daily frequency data to identify event signals and construct a capital channel strategy [1][13] - Model Construction Process: 1. Define "low volume" events: - Closing price is in the bottom 10% percentile of the past 120 trading days - Trading volume exceeds the average of the past 120 trading days by 1.5 standard deviations 2. Define "high volume" events: - Closing price is in the top 90% percentile of the past 120 trading days - Trading volume exceeds the average of the past 120 trading days by 1.5 standard deviations [13] 3. Construct a capital channel strategy: - Set up 4 capital channels, each with a holding period of 20 trading days - At the beginning of each week, review the past 5 trading days and identify stocks that triggered high/low volume signals - Equally allocate funds to the identified stocks at the beginning of the week and hold for 20 trading days - Calculate the net value of the capital channel portfolio by summing the net values of the 4 channels [18] - Model Evaluation: The daily frequency "high/low volume" signals showed that the average excess return peaked around 20-25 trading days after the signal was triggered, but the returns were volatile and did not provide stable incremental returns [1][13][18] 2. Model Name: High-Frequency "High/Low Volume" Event Cluster - Model Construction Idea: Use high-frequency micro-level price and volume data to construct more stable "high/low volume" event clusters, which are less correlated and more effective [2][25] - Model Construction Process: 1. Event Identification: - Define "high/low price" using minute-level closing price data - Define "high/low volume" using minute-level trading volume data, considering factors such as "who's volume," "direction of volume," and "type of volume" [26][29][32] 2. Signal Definition: - Combine "high/low price" and "high/low volume" using two methods: - "Price first, volume second": Identify high/low price points first, then check if volume is high - "Volume first, price second": Identify high volume points first, then check if price is high/low [42][43] 3. Signal Screening and Synthesis: - Produce thousands of event signals by combining different identification methods - Evaluate the effectiveness and correlation of each signal - Retain effective and low-correlation signals to form "high volume event cluster" and "low volume event cluster" - Synthesize signals to construct comprehensive "high volume" and "low volume" signals [26][44][45] - Model Evaluation: The high-frequency "low volume" comprehensive signal provided stable positive excess returns, while the "high volume" comprehensive signal demonstrated strong negative selection effects [50][57] 3. Model Name: Combined "High/Low Volume" Signal - Model Construction Idea: Combine the positive selection effect of the "low volume" signal with the negative selection effect of the "high volume" signal to enhance the performance of the capital channel strategy [3][58] - Model Construction Process: 1. Use the "low volume" comprehensive signal to pre-screen the stock pool 2. Exclude stocks that triggered the "high volume" comprehensive signal in the past 5 trading days 3. Construct a capital channel strategy: - Set up 4 capital channels, each with a holding period of 20 trading days - At the beginning of each week, review the past 5 trading days and identify stocks that meet the combined signal criteria - Equally allocate funds to the identified stocks at the beginning of the week and hold for 20 trading days - Calculate the net value of the capital channel portfolio by summing the net values of the 4 channels [58] - Model Evaluation: The combination of the two signals improved the performance of the capital channel strategy, enhancing both returns and stability [58][60] --- Model Backtesting Results 1. Daily Frequency "High/Low Volume" Signal - Low Volume Signal: - Annualized excess return: 7.67% - IR: 2.22 - Maximum drawdown: 4.68% [50][51] - High Volume Signal: - Annualized excess return: -10.16% - IR: -0.44 - Maximum drawdown: 8.47% [57] 2. High-Frequency "High/Low Volume" Event Cluster - Low Volume Comprehensive Signal: - Annualized excess return: 7.67% - IR: 2.22 - Maximum drawdown: 4.68% [50][51] - High Volume Comprehensive Signal: - Annualized excess return: -10.16% - IR: -0.44 - Maximum drawdown: 8.47% [57] 3. Combined "High/Low Volume" Signal - Combined Signal: - Annualized excess return: 9.14% - IR: 2.42 - Maximum drawdown: 3.70% [60] --- Quantitative Factors and Construction Methods 1. Factor Name: Low Volume Signal - Factor Construction Idea: Identify stocks with low prices and high trading volumes as potential candidates for positive returns [13] - Factor Construction Process: 1. Define "low price" as the closing price in the bottom 10% percentile of the past 120 trading days 2. Define "high volume" as trading volume exceeding the average of the past 120 trading days by 1.5 standard deviations 3. Combine the two conditions to identify "low volume" events [13] - Factor Evaluation: The low volume signal showed positive returns, peaking around 20-25 trading days after the signal was triggered, but the returns were volatile [1][13] 2. Factor Name: High Volume Signal - Factor Construction Idea: Identify stocks with high prices and high trading volumes as potential candidates for negative returns [13] - Factor Construction Process: 1. Define "high price" as the closing price in the top 90% percentile of the past 120 trading days 2. Define "high volume" as trading volume exceeding the average of the past 120 trading days by 1.5 standard deviations 3. Combine the two conditions to identify "high volume" events [13] - Factor Evaluation: The high volume signal showed negative returns, with stocks underperforming after the signal was triggered [15][18] --- Factor Backtesting Results 1. Low Volume Signal - Annualized excess return: 7.67% - IR: 2.22 - Maximum drawdown: 4.68% [50][51] 2. High Volume Signal - Annualized excess return: -10.16% - IR: -0.44 - Maximum drawdown: 8.47% [57]