中邮因子周报：价值风格占优，风格切换显现-20251013

• Barra style factors: The report tracks various style factors including Beta, Market Cap, Momentum, Volatility, Non-linear Market Cap, Valuation, Liquidity, Profitability, Growth, and Leverage. Each factor is constructed using specific financial metrics and formulas. For example, the Profitability factor combines analyst forecast earnings price ratio, inverse price-to-cash flow ratio, and inverse price-to-earnings ratio (TTM), among others. The Growth factor incorporates earnings growth rate and revenue growth rate. These factors are used to evaluate stocks based on their historical and financial characteristics [13][14][15]. - GRU factors: GRU factors are derived from different training objectives, such as predicting future one-day close-to-close or open-to-open returns. Examples include close1d, open1d, barra1d, and barra5d. These factors are constructed using GRU models trained on historical data to forecast short-term stock movements. GRU factors showed strong performance, with most models achieving positive multi-period returns, except for barra1d, which experienced some drawdowns [20][28][32]. - Factor testing methodology: Factors are tested using a long-short portfolio approach. At the end of each month, stocks are ranked based on the latest factor values, with the top 10% being long positions and the bottom 10% being short positions. The portfolios are equally weighted, and factors are industry-neutralized before testing. This methodology ensures robust evaluation of factor performance across different market conditions [15][16][31]. - Factor performance results: - Style factors: Valuation, Profitability, and Leverage factors showed strong long performance, while Beta, Liquidity, and Momentum factors performed well on the short side [15][16]. - Technical factors: Across various time windows, low momentum and low volatility stocks generally outperformed, while high volatility and high momentum stocks underperformed. For example, the 60-day momentum factor showed a negative return of -3.11% in the last month but a positive return of 2.12% over the last six months [19][26][30]. - GRU factors: GRU models like barra1d achieved a year-to-date excess return of 5.22%, while barra5d and open1d also delivered strong multi-period returns. However, barra1d experienced a weekly drawdown of -1.65% [20][32][33]. - Multi-factor portfolio performance: The multi-factor portfolio outperformed the benchmark (CSI 1000 Index) by 1.35% over the past week. GRU-based models also showed strong excess returns, ranging from 0.68% to 1.60% over the same period. Year-to-date, the barra1d model achieved an excess return of 5.22% [32][33][34].