Quantitative Models and Factor Construction Factor Names and Construction Details - **Factor Name: Trend** - **Construction Idea**: Captures the market's preference for trend-following strategies, using exponential weighted moving averages (EWMA) with different half-lives to measure price trends[11][16] - **Construction Process**: - **Trend_120**: $ \text{EWMA(halflife=20)}/\text{EWMA(halflife=120)} $ - **Trend_240**: $ \text{EWMA(halflife=20)}/\text{EWMA(halflife=240)} $[16] - **Evaluation**: Demonstrates strong performance in short-term market environments, reflecting increased preference for trend-following strategies[11] - **Factor Name: Certainty** - **Construction Idea**: Measures market confidence in stable and predictable investments, using metrics like institutional holdings and analyst coverage[16] - **Construction Process**: - **Instholder Pct**: Proportion of institutional holdings - **Cov**: Analyst coverage adjusted for market capitalization - **Listdays**: Number of days since listing[16] - **Evaluation**: Improved performance indicates restored market confidence in certainty-driven strategies[11] - **Factor Name: Value** - **Construction Idea**: Focuses on valuation metrics such as book-to-price (BP) and earnings yield (EP)[16] - **Construction Process**: - **BP**: $ \text{Net Assets}/\text{Market Value} $ - **EP**: $ \text{Earnings}/\text{Market Value} $[16] - **Evaluation**: Shows recovery in market preference for value-oriented investments[11] - **Factor Name: Liquidity** - **Construction Idea**: Assesses the impact of liquidity on asset pricing using turnover rates and liquidity betas[16] - **Construction Process**: - **TO**: Average logarithmic turnover over 243 days - **Liquidity Beta**: Regression of individual stock turnover against market turnover[16] - **Evaluation**: Underperformed significantly, reflecting reduced demand for high-liquidity assets[12] - **Factor Name: Volatility** - **Construction Idea**: Measures the impact of price volatility on asset returns using historical and idiosyncratic volatility metrics[16] - **Construction Process**: - **Stdvol**: Standard deviation of returns over 243 days - **Ivff**: Idiosyncratic volatility from Fama-French 3-factor model over 243 days[16] - **Evaluation**: Weak performance indicates declining interest in high-volatility assets[12] - **Factor Name: Momentum** - **Construction Idea**: Captures the continuation of price trends over different time horizons[16] - **Construction Process**: - **UMR_1Y**: Risk-adjusted momentum over 12 months - **UMR_6M**: Risk-adjusted momentum over 6 months[16] - **Evaluation**: Mixed results, with long-term momentum factors underperforming[12] Factor Backtesting Results - **Trend Factor** - Weekly return: 2.26%[11] - Monthly return: 2.98%[13] - YTD return: -3.81%[13] - 1-year return: 24.24%[13] - Historical annualized return: 14.10%[13] - **Certainty Factor** - Weekly return: 1.36%[11] - Monthly return: -2.87%[13] - YTD return: -11.74%[13] - 1-year return: -20.09%[13] - Historical annualized return: 2.63%[13] - **Value Factor** - Weekly return: 0.78%[11] - Monthly return: -2.14%[13] - YTD return: -10.78%[13] - 1-year return: -27.42%[13] - Historical annualized return: 7.14%[13] - **Liquidity Factor** - Weekly return: -3.85%[12] - Monthly return: 0.07%[13] - YTD return: 15.79%[13] - 1-year return: 29.31%[13] - Historical annualized return: -3.52%[13] - **Volatility Factor** - Weekly return: -2.83%[12] - Monthly return: -1.05%[13] - YTD return: 5.31%[13] - 1-year return: 28.00%[13] - Historical annualized return: -13.15%[13] - **Momentum Factor** - Weekly return (1-year UMR): 0.15%[24] - Monthly return (1-year UMR): 0.21%[24] - YTD return (1-year UMR): 1.69%[24] - 1-year return (1-year UMR): 1.22%[24] - Historical annualized return (1-year UMR): 3.87%[24] MFE Portfolio Construction - **Construction Process**: - Objective: Maximize single-factor exposure while controlling for industry, style, and stock-specific constraints - Optimization Model: $ \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} $[61][62] - Constraints: - Style and industry exposure limits - Stock weight deviation limits - Turnover rate limits[64][65] - Backtesting: Monthly rebalancing, transaction cost of 0.3% applied, and performance evaluated against benchmarks[66]

Group 1 - The core viewpoint of the article is to track and analyze the performance of various index enhancement portfolios and the factors influencing stock selection across different indices [1][2][3]. Group 2 - The performance of the HuShen 300 index enhancement portfolio showed an excess return of 0.54% for the week and 2.44% year-to-date [5][19]. - The performance of the Zhongzheng 500 index enhancement portfolio indicated an excess return of 1.29% for the week and 4.77% year-to-date [5][21]. - The Zhongzheng 1000 index enhancement portfolio achieved an excess return of 1.67% for the week and 6.24% year-to-date [5][21]. - The Zhongzheng A500 index enhancement portfolio reported an excess return of 0.21% for the week and 5.19% year-to-date [5][25]. Group 3 - In the HuShen 300 component stocks, factors such as expected PEG, quarterly ROE, and quarterly EP performed well [6][4]. - In the Zhongzheng 500 component stocks, factors like three-month reversal, one-month reversal, and three-month turnover showed strong performance [6][8]. - For the Zhongzheng 1000 component stocks, one-month reversal, specificity, and three-month reversal were notable factors [6][10]. - In the Zhongzheng A500 index component stocks, three-month reversal, expected PEG, and expected EPTTM were effective factors [6][12]. - Among public fund heavy stocks, one-month reversal, three-month reversal, and expected PEG were the best-performing factors [6][14]. Group 4 - The public fund index enhancement products for HuShen 300 had a maximum excess return of 0.57%, a minimum of -0.34%, and a median of 0.05% for the week [19]. - The Zhongzheng 500 index enhancement products had a maximum excess return of 1.06%, a minimum of -0.28%, and a median of 0.25% for the week [21]. - The Zhongzheng 1000 index enhancement products reported a maximum excess return of 0.97%, a minimum of -0.55%, and a median of 0.23% for the week [21]. - The Zhongzheng A500 index enhancement products had a maximum excess return of 0.58%, a minimum of -0.49%, and a median of 0.02% for the week [25].