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东方因子周报:Growth风格登顶,EPTTM一年分位点因子表现出色-20250602
Orient Securities· 2025-06-02 08:15
Quantitative Models and Factor Construction Factor Names and Construction - **Factor Name: EPTTM One-Year Percentile** - **Construction Idea**: Measures the percentile rank of the earnings-to-price ratio (EPTTM) over the past year to capture valuation trends[6][17] - **Construction Process**: - Calculate the earnings-to-price ratio (EPTTM) for each stock - Determine the percentile rank of the current EPTTM relative to its distribution over the past year[17] - **Evaluation**: Demonstrated strong performance in certain indices like CSI 1000 and CSI All Share, indicating its effectiveness in capturing valuation signals[6][33][47] - **Factor Name: Pre-Expected PEG** - **Construction Idea**: Combines price-to-earnings ratio with expected growth rates to evaluate valuation adjusted for growth[17] - **Construction Process**: - Calculate the price-to-earnings ratio (PE) - Divide PE by the expected growth rate of earnings to derive the PEG ratio - Use analyst consensus forecasts for expected growth rates[17] - **Evaluation**: Exhibited strong performance in indices like CSI 800 and CSI 500, suggesting its utility in growth-adjusted valuation analysis[6][29][33] - **Factor Name: Six-Month UMR** - **Construction Idea**: Captures momentum adjusted for risk over a six-month window[17] - **Construction Process**: - Calculate the cumulative return over the past six months - Adjust for risk using a volatility or beta-based measure - Normalize the adjusted return to derive the UMR score[17] - **Evaluation**: Consistently effective across multiple indices, including CSI 500 and CSI 1000, highlighting its robustness in momentum strategies[6][25][33] - **Factor Name: Standardized Unexpected Earnings (SUE)** - **Construction Idea**: Measures the deviation of actual earnings from analyst expectations, standardized by the forecast error[17] - **Construction Process**: - Calculate the difference between actual and expected earnings - Standardize this difference using the standard deviation of forecast errors - Derive the SUE score for each stock[17] - **Evaluation**: Effective in identifying earnings surprises, with strong performance in CSI 500 and CSI All Share indices[6][25][47] Factor Backtesting Results - **EPTTM One-Year Percentile** - CSI 1000: Weekly return of 1.09%, monthly return of 0.83%, annualized return of 5.54%[6][33] - CSI All Share: Weekly return of 1.09%, monthly return of -0.34%, annualized return of -4.16%[6][47] - **Pre-Expected PEG** - CSI 800: Weekly return of 0.66%, monthly return of 2.66%, annualized return of 3.11%[6][29] - CSI 500: Weekly return of 0.27%, monthly return of 1.02%, annualized return of -1.79%[6][25] - **Six-Month UMR** - CSI 500: Weekly return of 0.76%, monthly return of 1.14%, annualized return of -3.98%[6][25] - CSI 1000: Weekly return of 0.32%, monthly return of 0.08%, annualized return of 2.58%[6][33] - **Standardized Unexpected Earnings (SUE)** - CSI 500: Weekly return of 0.55%, monthly return of -0.06%, annualized return of 1.46%[6][25] - CSI All Share: Weekly return of 0.32%, monthly return of -0.46%, annualized return of -4.36%[6][47] MFE Portfolio Construction - **Model Description**: Maximized Factor Exposure (MFE) portfolios are constructed to maximize exposure to a single factor while controlling for constraints such as industry and style exposures, stock weight limits, and turnover[61][62] - **Optimization Formula**: $$ \begin{array}{ll} \max & f^{T}w \\ \text{s.t.} & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & 0 \leq w \leq l \\ & 1^{T}w = 1 \\ & \Sigma|w-w_{0}| \leq to_{h} \end{array} $$ - **Explanation**: The objective function maximizes factor exposure, subject to constraints on style, industry, stock weights, and turnover[61][62] - **Evaluation**: Effective in isolating factor performance under realistic portfolio constraints, providing a robust framework for factor validation[61][65]
东方因子周报:Growth风格登顶,单季ROE因子表现出色-20250518
Orient Securities· 2025-05-18 14:43
Quantitative Factors and Construction Methods - **Factor Name**: Single-quarter ROE **Construction Idea**: This factor measures the return on equity (ROE) for a single quarter, reflecting the profitability of a company relative to its equity base[2][18] **Construction Process**: The formula for single-quarter ROE is: $ Quart\_ROE = \frac{Net\ Income \times 2}{Beginning\ Equity + Ending\ Equity} $ Here, "Net Income" represents the net profit for the quarter, and "Beginning Equity" and "Ending Equity" are the equity values at the start and end of the quarter, respectively[18] **Evaluation**: This factor performed well in the CSI All Share Index space during the past week, indicating its effectiveness in identifying profitable stocks[2][42] - **Factor Name**: Single-quarter ROA **Construction Idea**: This factor evaluates the return on assets (ROA) for a single quarter, assessing how efficiently a company utilizes its assets to generate profits[18] **Construction Process**: The formula for single-quarter ROA is: $ Quart\_ROA = \frac{Net\ Income \times 2}{Beginning\ Assets + Ending\ Assets} $ "Net Income" is the quarterly net profit, while "Beginning Assets" and "Ending Assets" are the total assets at the start and end of the quarter, respectively[18] **Evaluation**: This factor also demonstrated strong performance in the CSI All Share Index space over the past week, highlighting its utility in asset efficiency analysis[2][42] - **Factor Name**: Standardized Unexpected Earnings (SUE) **Construction Idea**: This factor captures the deviation of actual earnings from expected earnings, standardized by the standard deviation of expected earnings, to measure earnings surprises[18] **Construction Process**: The formula for SUE is: $ SUE = \frac{Actual\ Earnings - Expected\ Earnings}{Standard\ Deviation\ of\ Expected\ Earnings} $ "Actual Earnings" refers to the reported earnings, while "Expected Earnings" and their standard deviation are derived from analyst forecasts[18] **Evaluation**: This factor showed significant positive performance in the National SME Index (CSI 2000) and the ChiNext Index spaces, indicating its effectiveness in identifying earnings surprises[36][39] Factor Backtesting Results - **Single-quarter ROE**: - CSI All Share Index: Weekly return of 1.46%, monthly return of 1.95%, annualized return over the past year of -1.73%, and historical annualized return of 4.88%[42][43] - **Single-quarter ROA**: - CSI All Share Index: Weekly return of 1.09%, monthly return of 1.33%, annualized return over the past year of 0.27%, and historical annualized return of 4.14%[42][43] - **Standardized Unexpected Earnings (SUE)**: - National SME Index (CSI 2000): Weekly return of 6.41%, monthly return of 19.22%, annualized return over the past year of 32.33%, and historical annualized return of 10.98%[36] - ChiNext Index: Weekly return of 7.76%, monthly return of 26.34%, annualized return over the past year of 44.74%, and historical annualized return of 7.82%[39] Composite Factor Portfolio Construction - **MFE Portfolio Construction**: **Idea**: The Maximized Factor Exposure (MFE) portfolio is designed to maximize the exposure to a single factor while controlling for constraints such as industry and style exposures, stock weight deviations, and turnover[55][59] **Optimization Model**: The optimization problem is formulated as: $ \begin{array}{ll} max & f^{T}w \\ s.t. & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & 0 \leq w \leq l \\ & 1^{T}w = 1 \\ & \Sigma|w-w_{0}| \leq to_{h} \end{array} $ Here, $f$ represents the factor values, $w$ is the weight vector, and the constraints include style, industry, stock weight, and turnover limits[55][58] **Evaluation**: The MFE portfolio approach ensures that factor effectiveness is tested under realistic constraints, making it a robust method for evaluating factor performance[55][59] MFE Portfolio Backtesting Results - **CSI 300 Index**: - Weekly excess return: Maximum 1.05%, minimum -0.81%, median 0.00%[46][49] - Monthly excess return: Maximum 3.00%, minimum -1.15%, median 0.30%[46][49] - **CSI 500 Index**: - Weekly excess return: Maximum 1.00%, minimum -0.08%, median 0.40%[50][52] - Monthly excess return: Maximum 2.73%, minimum -0.42%, median 0.99%[50][52] - **CSI 1000 Index**: - Weekly excess return: Maximum 0.82%, minimum -0.26%, median 0.28%[53][54] - Monthly excess return: Maximum 3.52%, minimum -0.08%, median 1.72%[53][54]