BOCIC(SH:601696) Bank of China Securities·2025-05-18 15:36Quantitative Models and Construction Methods 1. Model Name: Changjiang Momentum Index - Model Construction Idea: The index uses the momentum effect in the A-share market, selecting stocks with strong momentum characteristics and relatively high liquidity[26][27] - Model Construction Process: - Momentum indicator = (1-year stock return) - (1-month stock return, excluding stocks with price limits)[26][27] - Select the top 100 stocks in the A-share market with the strongest momentum characteristics and relatively high liquidity as index constituents[26][27] - Model Evaluation: The index effectively represents the overall trend of stocks with the strongest momentum characteristics in the A-share market[26][27] 2. Model Name: Changjiang Reversal Index - Model Construction Idea: The index captures the reversal effect in the A-share market, selecting stocks with strong reversal characteristics and good liquidity[28] - Model Construction Process: - Screening indicator = 1-month stock return[28] - Select the top 100 stocks in the A-share market with the strongest reversal characteristics and good liquidity as index constituents[28] - Weight the constituents based on their average daily trading volume over the past three months[28] - Model Evaluation: The index aims to accurately represent the overall performance of stocks with high reversal characteristics in the A-share market during different phases[28] --- Model Backtesting Results 1. Changjiang Momentum Index - Relative Return (Momentum vs. Reversal): - 1 week: -0.2% - 1 month: 5.5% - Year-to-date: 8.5%[26][27] 2. Changjiang Reversal Index - Relative Return (Reversal vs. Momentum): - 1 week: 0.2% - 1 month: -5.5% - Year-to-date: -8.5%[26][27] --- Quantitative Factors and Construction Methods 1. Factor Name: Style Crowdedness - Factor Construction Idea: Measures the crowdedness of different investment styles (e.g., growth, dividend, small-cap, large-cap) based on turnover rates[34][120] - Factor Construction Process: - Calculate the z-score standardized turnover rate of each style index over the past n trading days[120] - Subtract the turnover rate of the Wind All A Index from the style index turnover rate[120] - Compute the rolling y-year percentile of the difference[120] - Parameters: - 6-month crowdedness: n = 126, rolling window = 3 years - 1-year crowdedness: n = 252, rolling window = 6 years[120] - Factor Evaluation: Provides insights into the relative popularity and valuation of different investment styles over time[34][120] 2. Factor Name: Style Excess Cumulative Net Value - Factor Construction Idea: Measures the relative performance of style indices compared to the Wind All A Index[121] - Factor Construction Process: - Base date: January 4, 2016[121] - Daily cumulative net value = (style index closing value) / (base date closing value)[121] - Excess cumulative net value = (style index cumulative net value) / (Wind All A cumulative net value)[121] - Factor Evaluation: Tracks the relative performance trends of different styles over time[121] --- Factor Backtesting Results 1. Style Crowdedness - Growth vs. Dividend: - Growth crowdedness: 0% (1-year percentile), unchanged from last week[34] - Dividend crowdedness: 16% (1-year percentile), down from 22% last week[34] - Small-cap vs. Large-cap: - Small-cap crowdedness: 0% (1-year percentile), down from 1% last week[38] - Large-cap crowdedness: 29% (1-year percentile), down from 32% last week[38] - Micro-cap vs. Fund-heavy: - Micro-cap crowdedness: 6% (1-year percentile), unchanged from last week[40] - Fund-heavy crowdedness: 6% (6-month percentile), unchanged from last week[40] 2. Style Excess Cumulative Net Value - Growth vs. Dividend: - 1 week: +0.4% - 1 month: +2.3% - Year-to-date: +0.6%[26][34] - Small-cap vs. Large-cap: - 1 week: -1.4% - 1 month: -0.5% - Year-to-date: +1.5%[26][38] - Micro-cap vs. Fund-heavy: - 1 week: +1.3% - 1 month: +10.8% - Year-to-date: +26.5%[26][40]