- The report tracks the performance of Guosen Financial Engineering's index enhancement portfolios, which are constructed based on benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices, aiming to consistently outperform their respective benchmarks [11][12][14] - The construction process of the index enhancement portfolios includes three main components: return prediction, risk control, and portfolio optimization [12] - The report monitors the performance of common stock selection factors across different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices, by constructing single-factor Maximized Factor Exposure (MFE) portfolios and tracking their relative excess returns [11][15][42] - The MFE portfolio construction process involves optimizing the portfolio to maximize single-factor exposure while controlling for various constraints such as industry exposure, style exposure, stock weight deviation, turnover rate, and component stock weight proportion [42][43][44] - The optimization model for MFE portfolios is expressed as follows: $\begin{array}{ll}max&f^{T}\ w\\ s.t.&s_{l}\leq X(w-w_{b})\leq s_{h}\\ &h_{l}\leq H(w-w_{b})\leq h_{h}\\ &w_{l}\leq w-w_{b}\leq w_{h}\\ &b_{l}\leq B_{b}w\leq b_{h}\\ &\mathbf{0}\leq w\leq l\\ &\mathbf{1}^{T}\ w=1\end{array}$ where `f` represents factor values, `w` is the stock weight vector, and constraints include style factor deviation, industry deviation, stock weight deviation, component stock weight proportion, and stock weight limits [42][43] - The report provides detailed performance tracking of single-factor MFE portfolios across different stock selection spaces, highlighting factors such as SP, SPTTM, EP, and others that performed well in specific indices like CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices [15][18][20][22][24][26] - The report also tracks the excess returns of public fund index enhancement products, including CSI 300, CSI 500, CSI 1000, and CSI A500, with detailed statistics on maximum, minimum, and median excess returns over different time periods [28][32][35][38][41]

Core Viewpoint - The report highlights the performance of various market factors and investment strategies, indicating a mixed performance across different stock pools and sectors, with certain factors yielding positive excess returns [4][7][8][9][10]. Group 1: Market Factor Performance - The overall market showed positive returns for the Beta factor (0.66%) and valuation factor (0.48%), while the market capitalization factor yielded negative returns (-0.80%), indicating a preference for small-cap stocks [4]. - In the CSI 300 stock pool, the best-performing factors included the 5-day average turnover rate (4.52%) and 5-day reversal (3.17%), while the total asset growth rate (-2.05%) and quarterly ROE (-1.16%) performed poorly [5]. - The CSI 500 stock pool saw strong performance from the 5-day reversal (3.80%) and quarterly operating profit growth rate (1.98%), but struggled with momentum-adjusted small caps (-2.41%) [5]. Group 2: Sector-Specific Factor Performance - Fundamental factors showed varied performance across sectors, with net asset per share and TTM operating profit factors performing well in the defense and leisure services sectors [6]. - Valuation factors such as BP and EP also yielded positive returns in the defense and leisure services industries, while residual volatility and liquidity factors performed well in the coal sector [6]. Group 3: Investment Strategy Performance - The PB-ROE-50 combination achieved positive excess returns across stock pools, with the CSI 500 pool gaining 1.38% and the CSI 800 pool gaining 2.54% [7]. - Public and private fund research selection strategies both generated positive excess returns, with public strategies outperforming the CSI 800 by 0.61% and private strategies by 3.43% [8]. - The block trading combination also achieved positive excess returns relative to the CSI All Index, with a gain of 0.86% [9]. - The targeted issuance combination outperformed the CSI All Index by 1.32%, indicating strong performance in this investment strategy [10].

- The Beta factor and valuation factor achieved positive returns of 0.66% and 0.48% respectively, while the size factor had a negative return of -0.80%[1][18] - In the CSI 300 stock pool, the best-performing factors this week were the 5-day average turnover rate (4.52%), 5-day reversal (3.17%), and price-to-book ratio factor (3.10%)[1][12] - In the CSI 500 stock pool, the best-performing factors this week were the 5-day reversal (3.80%), single-quarter operating profit growth rate (1.98%), and price-to-sales ratio TTM reciprocal (1.65%)[1][14] - In the liquidity 1500 stock pool, the best-performing factors this week were the post-morning return factor (2.18%), 5-day reversal (2.17%), and standardized unexpected income (1.77%)[2][16] - The PB-ROE-50 portfolio achieved positive excess returns in various stock pools this week, with excess returns of 1.38% in the CSI 500 stock pool, 2.54% in the CSI 800 stock pool, and 4.23% in the entire market stock pool[2][23] - The public research stock selection strategy and private research tracking strategy achieved positive excess returns this week, with the public research stock selection strategy achieving an excess return of 0.61% relative to the CSI 800, and the private research tracking strategy achieving an excess return of 3.43% relative to the CSI 800[3][25] - The block trading portfolio achieved a positive excess return of 0.86% relative to the CSI All Share Index this week[3][29] - The directed issuance portfolio achieved a positive excess return of 1.32% relative to the CSI All Share Index this week[3][35]

Bond Market Investment Rating The report does not explicitly mention the industry investment rating. Core Views - As the annual report and performance forecast disclosure window opens, the market is expected to return to the performance mainline, with the sustainability of theme investments likely to weaken and valuation factors expected to strengthen [1][21]. - In the past week, after the equity market's volume increased and prices soared, the market style is expected to enter a stage of balanced development. The small and medium - cap stocks showed strong performance, and the market style is expected to shift from theme - driven to balanced allocation [1][10]. - Recently, the volatility and volume - price correlation style has been strong, while valuation factors have not been fully priced. Investors need to seize strong varieties while strengthening drawdown control and valuation constraints [2][11]. - The spring market is not over yet. High - quality companies with solid fundamentals and better - than - expected performance are expected to achieve excess returns and become the core mainline in the second half of the spring market [3][21]. Summary by Directory 1. Convertible Bond Weekly Thinking - **Market Style and Allocation Tendency**: After the equity market's volume increased and prices soared, the market style is expected to enter a stage of balanced development. The small and medium - cap stocks showed strong performance. The market style is expected to shift from theme - driven to balanced allocation, and the convertible bond market style is expected to return to relative balance with the equity market [1][10]. - **Style Performance and Strategy**: The volatility and volume - price correlation style has been strong, while valuation factors have not been fully priced. The volatility style is relatively stable, but the momentum and volume - price correlation styles are weakened by some targets. Investors need to seize strong varieties while strengthening drawdown control and valuation constraints [2][11]. - **Fund Flow and Preference**: In the past week, the risk preference of funds continued to be cautious, and the allocation idea was still centered on defense and stability. Bond ETFs were actively traded, and the market was in a stage of high - level shock with obvious industry and style rotation characteristics [12]. - **Future Market Outlook**: As the annual report and performance forecast disclosure window opens, the market is expected to return to the performance mainline. High - quality companies with solid fundamentals and better - than - expected performance are expected to achieve excess returns, mainly due to the mean - reversion of market sentiment, the change of incremental fund attributes, and the return of the valuation constraint mechanism [3][21]. 1.1 Convertible Bond Market - **Index Performance**: Different convertible bond indexes showed different performance in different time periods. For example, the Wind Convertible Bond Information Technology Index had a weekly increase of 2.52%, and the Wind Convertible Bond High - price Index had a weekly increase of 3.45% [23]. 1.2 Convertible Bond Individual Securities - **Ranking of Individual Securities**: The report presents the top ten and bottom ten individual convertible bonds in terms of weekly gains and losses, such as Huayi Convertible Bond leading the gainers and Zai 22 Convertible Bond leading the losers [24][26]. 1.3 Convertible Bond Valuation - **Valuation Trends**: The report shows the valuation trends of bond - type, balanced, and equity - type convertible bonds, as well as the valuation trends of convertible bonds with different parities [28][30][34]. 1.4 Convertible Bond Price - **Price Indicators**: The report shows the proportion trend of high - price bonds and the median price trend of convertible bonds [31][38][39].

Core Viewpoint - The article provides a comprehensive analysis of market performance, highlighting the varying returns of different factors across multiple stock pools, indicating a mixed investment environment with specific factors outperforming others [4][5][6]. Factor Performance - In the overall market stock pool, valuation and profitability factors achieved positive returns of 0.27% and 0.25% respectively, while market capitalization factors yielded negative returns of -0.91% and -0.51%, suggesting a small-cap style dominance [4]. - In the CSI 300 stock pool, the best-performing factors included quarterly ROE YoY (2.31%), quarterly ROE (1.81%), and P/E ratio (1.51%), while total asset growth rate (-1.28%) and quarterly operating profit YoY growth rate (-0.83%) were among the worst [5]. - In the CSI 500 stock pool, the top factors were P/B ratio (1.78%), standardized expected external income (1.74%), and operating cash flow ratio (1.28%), with quarterly net profit YoY growth rate (-1.19%) and quarterly operating profit YoY growth rate (-1.06%) performing poorly [5]. - In the liquidity 1500 stock pool, the best factors were P/E ratio (1.44%), downside volatility ratio (1.24%), and P/B ratio (1.17%), while quarterly net profit YoY growth rate (-1.00%) and quarterly operating revenue YoY growth rate (-0.82%) lagged [5]. Industry Factor Performance - Fundamental factors showed varied performance across industries, with net asset growth rate, net profit growth rate, and earnings per share factors yielding consistent positive returns in the media and textile sectors [6]. - Valuation factors, particularly the BP factor, demonstrated significant positive returns across most industries, while the EP factor also showed consistent positive returns in the comprehensive sector [6]. - The small-cap style was notably prominent across most industries, while large-cap styles were significant in defense, non-bank financials, non-ferrous metals, and oil and petrochemical sectors [7]. Combination Tracking - The PB-ROE-50 combination recorded negative excess returns across all stock pools, with the CSI 500 pool showing an excess return of -0.02% and the overall market pool at -0.75% [8]. - Institutional research combinations, including public and private fund strategies, also reported negative excess returns, with public strategies yielding -0.43% and private strategies -1.92% relative to the CSI 800 [9]. - The block trading combination underperformed relative to the CSI All Index, with an excess return of -0.68% [10]. - Conversely, the targeted issuance combination achieved positive excess returns of 1.46% relative to the CSI All Index [11].

Quantitative Models and Factor Construction Quantitative Models and Construction Methods 1. **Model Name**: Dynamic Factor Adjustment Model **Model Construction Idea**: Combines factor momentum and reversal characteristics to dynamically adjust factor selection based on historical performance and failure probabilities[4][80][82] **Model Construction Process**: - Evaluate factor momentum using the average RankIC over the past 6 months and the average RankICIR over the past 3-12 months[4][82] - Calculate conditional failure probabilities by rolling one year of historical data to assess the likelihood of a factor transitioning from effective to ineffective[74][87] - Exclude factors with high failure probabilities and assign scores based on momentum and failure probabilities. Select the top N factors with the highest scores for equal-weighted scoring in each period[82][87][88] **Model Evaluation**: The model effectively balances momentum and reversal characteristics, reducing the impact of unstable factors and improving robustness in factor selection[82][87] 2. **Model Name**: "2+3" Dynamic Factor Model for Small-Cap Stocks **Model Construction Idea**: Combines two fixed factors (valuation and volatility) with three dynamically selected high-momentum factors to construct a robust small-cap stock selection model[98][99] **Model Construction Process**: - Fixed factors: Valuation (BTOP) and volatility (VOLATILITY) are always included due to their stable and significant performance in small-cap pools[98][99] - Dynamic factors: Exclude factors with conditional failure probabilities above 80% and select the top 3 factors based on medium- and long-term momentum scores[98][99] - Construct a portfolio of 50 equally weighted stocks based on the selected factors[98][103] **Model Evaluation**: The model demonstrates strong performance in small-cap pools, with high momentum and low reversal failure probabilities, making it robust against overfitting[98][103] 3. **Model Name**: "Exclusion + Scoring" Model for Large-Cap Stocks **Model Construction Idea**: Focuses on stricter exclusion of high-failure-probability factors and integrates failure information into the scoring process for large-cap stock selection[109][110] **Model Construction Process**: - Exclude factors with conditional failure probabilities above 70%[109][110] - Combine failure indicators into the momentum scoring model, selecting the top 5 factors with the highest comprehensive scores[109][110] - Construct a portfolio of 50 equally weighted stocks based on the selected factors[109][113] **Model Evaluation**: The model effectively addresses the high sensitivity and extreme reversals in large-cap pools, improving stability and performance[109][113] Model Backtesting Results 1. **Dynamic Factor Adjustment Model**: - Annualized return: 8.83% - Sharpe ratio: 0.42 - Excess annualized return: 11.47% - Maximum drawdown: 38.67%[103] 2. **"2+3" Dynamic Factor Model for Small-Cap Stocks**: - Annualized return: 8.83% - Sharpe ratio: 0.42 - Excess annualized return: 11.47% - Maximum drawdown: 38.67%[103] 3. **"Exclusion + Scoring" Model for Large-Cap Stocks**: - Annualized return: 8.40% - Sharpe ratio: 0.40 - Excess annualized return: 8.32% - Maximum drawdown: 36.40%[113] Quantitative Factors and Construction Methods 1. **Factor Name**: Valuation (BTOP) **Factor Construction Idea**: Measures the book-to-price ratio to capture undervalued stocks[8][39] **Factor Construction Process**: Calculate the ratio of book value to current market value for each stock[8][39] **Factor Evaluation**: Demonstrates stable and significant performance in small-cap pools, with strong selection ability in various market conditions[39][98] 2. **Factor Name**: Volatility (VOLATILITY) **Factor Construction Idea**: Measures the residual volatility of stock returns to identify low-risk stocks[8][50] **Factor Construction Process**: Calculate the standard deviation of residuals from a time-series regression of stock returns[8][50] **Factor Evaluation**: Performs well in both small-cap and large-cap pools, with low failure probabilities and consistent selection ability[50][98] 3. **Factor Name**: Earnings (EARNING) **Factor Construction Idea**: Measures earnings yield to capture profitability[8][39] **Factor Construction Process**: Calculate the ratio of earnings to market value for each stock[8][39] **Factor Evaluation**: Strong selection ability in large-cap pools, with stable performance across different market conditions[39][113] Factor Backtesting Results 1. **Valuation (BTOP)**: - RankICIR: Consistently ranks in the top 2 across small-cap pools[39][98] 2. **Volatility (VOLATILITY)**: - RankICIR: Demonstrates stable negative expression across all pools, with low failure probabilities[50][98] 3. **Earnings (EARNING)**: - RankICIR: Strong performance in large-cap pools, with high selection ability and stable expression[39][113]

Group 1: Report Industry Investment Rating - No relevant content found Group 2: Core Views of the Report - In the medium - term, the expectation of a slow - bull market in the equity market remains solid. With a temporary decline in market risk appetite, the dumbbell strategy is expected to achieve excess returns. The valuation factor and volatility factor are expected to strengthen marginally. In the short - term, attention should be paid to the risk of excess drawdown due to style mismatch in the convertible bond market. It is recommended to maintain a neutral position to enjoy the excess returns brought by the spill - over of the equity bull market, taking into account both growth and defense [1][22] Group 3: Summary by Relevant Catalog 1. Convertible Bond Weekly Thinking - From November 10 to November 14, 2025, the style of the convertible bond market changed significantly, with the tech - growth style retreating and the energy and consumption indices strengthening. The main line of the convertible bond market is not clear, and sector rotation has accelerated. The technology sectors represented by AI computing power and semiconductors have declined, while the power equipment and photovoltaic industries have performed well. The dividend style has strengthened due to risk - aversion and overseas tech valuation bubbles. As the year - end approaches, some investors may lock in profits, and the market is likely to be dominated by rotation, increasing the difficulty of convertible bond trading [11] - In the volatile market, the valuation of bond - like convertible bonds is firm, and the market tends to be defensive in the short - term. As of November 14, 2025, the median price of convertible bonds is close to 134 yuan, a recent high. The market style has shifted from offensive to defensive, with bond - biased convertible bonds performing better than equity - biased ones. The pure - bond premium rate of bond - like convertible bonds has been rising. In terms of valuation, the convertible bond valuation is oscillating at a high level, with the premium rate of bond - like convertible bonds at 84.51%, the balanced convertible bonds at about 22.66%, and the equity - like convertible bonds at 10.18%, down about 1.13 percentage points from the recent high [3][12] - In the volatile market, attention should be paid to the tail risk of the momentum factor to avoid the risk of excess return drawdown caused by trend reversal. The convertible bond momentum factor has performed well this year, mainly because it has captured the "trend effect" in the convertible bond market since Q2 2025. However, with the continuous small - scale outflow of passive funds represented by ETFs, there is a possibility of style switching in the convertible bond market. The momentum effect brought by liquidity premium may be the source of excess returns in the convertible bond market this year. In the short - term, attention should be paid to the risk of excess drawdown due to style mismatch. As the equity market enters the performance verification stage, the valuation factor and volatility factor are expected to strengthen, enabling investors to enjoy the excess returns from the value regression of undervalued convertible bonds and through high - selling and low - buying in the volatile market [4][14][19] - In November, investors are recommended to focus on convertible bonds such as Shangyin, Shouhua, Aola, Jingke, Baolong, Keshun, Yingbo, Wei, Jin 25, and Anji [23] 2. Convertible Bond Market Tracking 2.1 Convertible Bond Market Conditions - The report provides the performance data of various convertible bond indices in different time periods (recent week, recent two weeks, since September, recent month, recent two months, recent half - year, and recent one - year), including the Wande Convertible Bond Energy Index, Wande Convertible Bond Materials Index, etc. [24] 2.2 Convertible Bond Individual Securities - The report shows the top ten and bottom ten individual convertible bonds in terms of price increase and decrease in the recent week [26][27] 2.3 Convertible Bond Valuation - The report presents the valuation trends of bond - like, balanced, and equity - like convertible bonds, as well as the valuation trends of convertible bonds with different parities [28][36] 2.4 Convertible Bond Price - The report shows the proportion trend of high - price bonds and the median price trend of convertible bonds [38]

Core Insights - The report highlights the strong performance of the CSI 1000 index, which achieved a return of 1.18% during the week of October 27-31, 2025, making it one of the top-performing indices [3][7]. - For the year, the CSI 1000 index has shown a return of 29.99%, outperforming the benchmark index by 3.99% [4][15]. Market Performance - In the week of October 27-31, 2025, the CSI 1000 and CSI 500 indices led in returns, with gains of 1.18% and 1.00%, respectively, while the STAR 50 and SSE 50 indices lagged with returns of -3.19% and -1.12% [3][7]. - Year-to-date, the Micro Index and ChiNext Index have performed exceptionally well, with returns of 67.31% and 48.84%, while the CSI Dividend and SSE 50 indices have underperformed, returning 0.83% and 12.17% [8]. Strategy Performance - The CSI 1000 index enhancement strategy yielded a return of 1.03% for the week, slightly underperforming the index return of 1.18%, resulting in an excess return of -0.15% [4][12]. - In October, the strategy achieved a return of 0.27%, outperforming the index, which had a return of -0.90%, leading to an excess return of 1.17% [14]. - For the year, the strategy's return stands at 29.99%, compared to the index's 26.00%, resulting in an excess return of 3.99% [15]. Investment Recommendations - The CSI 1000 index is noted for its strong performance in 2025, attributed to its strategic focus on sectors such as new energy, semiconductors, and medical devices, which are considered frontier industries [5][18]. - The index is characterized by significant valuation elasticity and policy expectations, making it a high-risk, high-volatility investment option as market risk appetite is expected to tighten towards year-end [5][18].

- The report tracks the performance of style factors, including momentum, beta, and liquidity factors, which showed strong long positions, while leverage, market capitalization, and valuation factors exhibited strong short positions[3][16] - The report includes the performance of fundamental factors across different stock pools, such as the CSI 300, CSI 500, and CSI 1000, highlighting that low valuation and high growth stocks were generally strong[5][6][7][20][22][25] - Technical factors' performance was mostly positive, with high volatility and long-term momentum stocks performing well, except for the 20-day momentum factor which showed negative performance[4][18][23][26] - The GRU factors' performance was weak overall, with the close1d model showing strong performance, while other models like open1d and barra1d experienced drawdowns[4][5][6][7][18][20][23][26] - The report details the construction and recent performance of the GRU long-only portfolios, noting that the barra1d model outperformed the CSI 1000 index by 0.38%, while the open1d and close1d models underperformed by 0.40%-0.53%[8][31][32] Factor Construction and Performance - **Barra Style Factors**: The report lists several style factors such as Beta, Market Cap, Momentum, Volatility, Non-linear Size, Valuation, Liquidity, Profitability, Growth, and Leverage, with detailed formulas for each[14][15] - **Fundamental Factors**: The report tracks various fundamental factors, including unexpected growth and growth-related financial factors, with mixed performance across different stock pools[4][5][6][7][18][20][22][25] - **Technical Factors**: The report includes several technical factors, such as 20-day momentum, 60-day momentum, 120-day momentum, and various volatility measures, with detailed performance metrics[4][18][23][26] Factor Performance Metrics - **Fundamental Factors**: - Operating Turnover: -1.14% (1 week), 4.19% (1 month), -11.23% (6 months), -11.52% (YTD), -1.86% (3-year annualized), 3.31% (5-year annualized)[19] - ROC: -0.68% (1 week), 0.89% (1 month), -10.51% (6 months), -10.59% (YTD), -13.06% (3-year annualized), -11.85% (5-year annualized)[19] - ROE Growth: 0.36% (1 week), 2.01% (1 month), 10.43% (6 months), 2.27% (YTD), 0.38% (3-year annualized), 2.61% (5-year annualized)[19] - **Technical Factors**: - 20-day Momentum: -0.73% (1 week), 0.66% (1 month), -8.17% (6 months), -12.18% (YTD), -13.19% (3-year annualized), -13.77% (5-year annualized)[19] - Median Deviation: -0.38% (1 week), -3.25% (1 month), -5.83% (6 months), -4.72% (YTD), -15.12% (3-year annualized), -15.62% (5-year annualized)[19] - 60-day Momentum: 0.35% (1 week), -3.31% (1 month), 2.64% (6 months), 5.08% (YTD), -12.82% (3-year annualized), -16.17% (5-year annualized)[19] GRU Model Performance - **GRU Long-Only Portfolios**: - open1d: -0.40% (1 week), -0.20% (1 month), 2.37% (3 months), 6.32% (6 months), 7.16% (YTD)[32] - close1d: -0.53% (1 week), -0.83% (1 month), 4.38% (3 months), 6.80% (6 months), 6.59% (YTD)[32] - barra1d: 0.38% (1 week), -0.25% (1 month), 0.85% (3 months), 2.85% (6 months), 3.78% (YTD)[32] - barra5d: 0.00% (1 week), -0.36% (1 month), 3.59% (3 months), 7.41% (6 months), 8.37% (YTD)[32] - Multi-Factor: -0.38% (1 week), -0.30% (1 month), 1.62% (3 months), 2.54% (6 months), 2.54% (YTD)[32]

Quantitative Models and Construction - **Model Name**: Three-dimensional Timing Framework **Construction Idea**: The model integrates liquidity, divergence, and prosperity indicators to assess market timing and risk levels[7][14][16] **Construction Process**: 1. **Liquidity Index**: Tracks market liquidity trends[22] 2. **Divergence Index**: Measures market disagreement levels[20] 3. **Prosperity Index**: Evaluates industrial prosperity trends[26] 4. Combines these three dimensions to form a comprehensive timing framework[14] **Evaluation**: Demonstrates stable performance in identifying market timing opportunities[16] - **Model Name**: Financing-Active Large Order Flow Intersection Strategy **Construction Idea**: Combines financing and large order flows to identify industries with strong capital inflows[34][40] **Construction Process**: 1. **Financing Flow Factor**: Neutralizes market capitalization and calculates the net financing buy-sell difference over a 50-day average[40] 2. **Active Large Order Flow Factor**: Neutralizes transaction volume and ranks net inflows over the past year, using a 10-day average[40] 3. Filters extreme industries and integrates both factors to enhance stability[40] **Evaluation**: Achieves stable annualized excess returns with reduced drawdowns compared to other strategies[40] Quantitative Models Backtesting Results - **Three-dimensional Timing Framework**: Historical performance shows stable risk assessment and timing capabilities[16] - **Financing-Active Large Order Flow Intersection Strategy**: - Annualized excess return: 13.5% - IR: 1.7[40] - Weekly absolute return: -1.6% - Weekly excess return: -0.1%[40] Quantitative Factors and Construction - **Factor Name**: Valuation Factors **Construction Idea**: Focuses on valuation metrics such as earnings yield and book-to-market ratios[46][47] **Construction Process**: 1. **Earnings Yield (ep_fy3)**: $ ep\_fy3 = \frac{1}{PE\_FY3} $ 2. **Book-to-Market Ratio (bp)**: $ bp = \frac{Shareholder\_Equity}{Market\_Value} $ 3. Neutralizes industry and market capitalization effects[46][48] **Evaluation**: Demonstrates strong performance across multiple timeframes and indices[46][48] - **Factor Name**: Growth Factors **Construction Idea**: Captures growth metrics such as revenue and profit growth rates[46][49] **Construction Process**: 1. **Revenue Growth (yoy_or)**: $ yoy\_or = \frac{Current\_Revenue - Previous\_Revenue}{Previous\_Revenue} $ 2. **Profit Growth (yoy_np)**: $ yoy\_np = \frac{Current\_Net\_Profit - Previous\_Net\_Profit}{Previous\_Net\_Profit} $ 3. Neutralizes industry and market capitalization effects[46][50] **Evaluation**: Performs better in large-cap indices and shows consistent excess returns[49][50] Quantitative Factors Backtesting Results - **Valuation Factors**: - Weekly excess return: 1.5%-2.18% - Monthly excess return: 1.46%-3.85%[48] - **Growth Factors**: - Weekly excess return: 1.52%-3.89% - Monthly excess return: 0.79%-3.02%[50] Quantitative Portfolios and Construction - **Portfolio Name**: Index Enhancement Portfolios **Construction Idea**: Adjusts factor selection based on research coverage to enhance index performance[51] **Construction Process**: 1. Divides stocks into high and low research coverage domains[51] 2. Applies suitable factors for each domain to optimize portfolio construction[51] **Evaluation**: Outperforms original index selection methods in terms of excess returns[51] Quantitative Portfolios Backtesting Results - **Index Enhancement Portfolios**: - **HS300**: - Weekly absolute return: -0.89% - Weekly excess return: 0.03% - Annualized excess return: 7.77%[52] - **CSI500**: - Weekly absolute return: 0.16% - Weekly excess return: 0.40% - Annualized excess return: 9.82%[52] - **CSI1000**: - Weekly absolute return: -0.58% - Weekly excess return: -0.74% - Annualized excess return: 9.26%[52]