Core Insights - The report highlights the current industry allocation of the Bank of China’s multi-strategy system, with significant positions in non-bank financials (11.7%), steel (11.0%), and comprehensive sectors (10.1%) [1] - The average weekly return for the CITIC primary industries was -0.4%, while the average return over the past month was 2.3% [3][10] - The report identifies the top-performing industries for the week as automotive (4.4%), electronics (4.4%), and electric equipment and new energy (4.1%), while the worst performers were banking (-5.6%), non-bank financials (-4.4%), and food and beverage (-3.6%) [3][10] Industry Performance Review - The report provides a detailed performance review of CITIC primary industries, indicating that the automotive sector has a year-to-date return of 34.4%, while electronics and electric equipment and new energy have returns of 48.0% and 36.0%, respectively [11] - The report notes that the composite strategy has achieved a cumulative return of 24.5% year-to-date, outperforming the CITIC primary industry equal-weight benchmark return of 22.2% by 2.2% [3] Valuation Risk Warning - The report employs a valuation warning system based on the PB ratio over the past six years, identifying industries with a PB ratio above the 95th percentile as overvalued [12][13] - Currently, the industries triggering high valuation warnings include retail, media, computing, and automotive, with their PB ratios exceeding the 95th percentile [13] Single Strategy Rankings and Recent Performance - The report outlines the top three industries based on the high profitability tracking strategy as non-bank financials, agriculture, and steel [15][16] - The report also details the performance of various strategies, with the S2 strategy (implied sentiment momentum tracking) highlighting mechanical, electric equipment and new energy, and comprehensive sectors as the top three industries [20] Macro Style Rotation Strategy - The macro style rotation strategy identifies the top six industries based on current macro indicators as comprehensive finance, computing, communication, national defense, electronics, and media [24] - The report emphasizes the importance of macroeconomic indicators in predicting industry performance, utilizing a multi-factor approach to assess industry exposure to various macroeconomic styles [22][23]

Core Insights - The report highlights the current industry allocation of the Bank of China’s multi-strategy system, with significant positions in non-ferrous metals (15.3%), non-bank financials (12.9%), and comprehensive sectors (7.3%) [1] - The average weekly return for the CITIC primary industries was -3.0%, while the average return over the past month was 3.1% [3][10] - The report identifies the top-performing industries for the week as electric equipment and new energy (2.4%), food and beverage (0.8%), and pharmaceuticals (0.5%), while the worst performers were defense and military (-11.9%), computers (-9.8%), and electronics (-9.7%) [3][10] Industry Performance Review - The report provides a detailed performance review of CITIC primary industries, indicating that the average weekly return was -3.0% and the average monthly return was 3.1% [10] - The top three industries by weekly performance were electric equipment and new energy (2.4%), food and beverage (0.8%), and pharmaceuticals (0.5%) [11] - The bottom three industries were defense and military (-11.9%), computers (-9.8%), and electronics (-9.7%) [11] Valuation Risk Warning - The report employs a valuation warning system based on the PB ratio over the past six years, identifying industries with a PB ratio above the 95th percentile as overvalued [14][15] - Currently, the industries triggering high valuation warnings include retail, media, computers, and defense and military, all exceeding the 95th percentile in PB valuation [15][16] Strategy Performance - The report outlines the performance of various strategies, with the composite strategy yielding a cumulative return of 20.2% year-to-date, outperforming the CITIC primary industry benchmark by 2.3% [3] - The highest excess return strategy was the industry profitability tracking strategy (S1), with an excess return of 5.1% compared to the benchmark [3] - The report indicates a shift in strategy allocations, increasing positions in upstream cyclical and pharmaceutical sectors while reducing exposure to TMT, consumer, and midstream cyclical sectors [3] Current Industry Rankings - The report ranks industries based on profitability expectations, with non-ferrous metals, non-bank financials, and agriculture being the top three [18] - The implied sentiment momentum strategy ranks communication, non-ferrous metals, and electronics as the top three industries based on market sentiment indicators [22] - The macroeconomic style rotation strategy identifies comprehensive finance, computers, communication, defense and military, electronics, and media as the top six industries based on macroeconomic indicators [25]

Core Insights - The report highlights the current industry allocation positions of the Bank of China’s multi-strategy system, with significant weights in non-bank financials (8.9%), comprehensive (8.5%), and telecommunications (7.7%) sectors [1] - The average weekly return for the CITIC primary industries is reported at 0.8%, with the telecommunications sector leading at 6.5% and banking lagging at -2.1% [3][10] - The report indicates that the composite strategy has achieved a cumulative return of 17.5% year-to-date, outperforming the CITIC primary industry equal-weight benchmark by 2.1% [3] Industry Performance Review - The top three performing industries for the week are telecommunications (6.5%), comprehensive financials (6.0%), and electric equipment & new energy (3.3%), while the worst performers are banking (-2.1%), national defense & military (-1.7%), and textiles & apparel (-1.7%) [3][10] - The report provides a detailed breakdown of weekly and monthly returns across various industries, indicating a strong performance in sectors like telecommunications and comprehensive financials [11] Valuation Risk Warning - The report employs a valuation warning system based on the PB ratio over the past six years, identifying industries with high valuation risks. Currently, the retail trade, national defense & military, media, and computer industries are flagged for high valuations, exceeding the 95% percentile [12][13] - The methodology for the valuation warning system involves excluding the top 10% of PB ratios to ensure robust estimates [12] Strategy Performance - The report outlines various strategies and their performance, with the highest excess return from the long-term reversal strategy (6.3%) and the lowest from the funds flow strategy (-2.0%) [3] - The current top three industries based on the high prosperity industry rotation strategy are non-bank financials, telecommunications, and non-ferrous metals [15][16] Macro Style Rotation - The macro style rotation strategy identifies the top six industries based on macroeconomic indicators, which include comprehensive financials, computers, media, national defense & military, comprehensive, and non-bank financials [21][23] - The report emphasizes the importance of macroeconomic indicators in predicting industry performance and the methodology used to rank industries based on their exposure to various styles [22] Emotional Momentum Tracking - The emotional momentum tracking strategy identifies the top three industries based on implied market sentiment, which are machinery, telecommunications, and light industry manufacturing [18][20] - This strategy focuses on capturing market sentiment before earnings expectations are published, utilizing daily return and turnover rate data [19]

Core Insights - The report highlights the current positioning of the Bank of China’s multi-strategy industry allocation system, with a comprehensive allocation of 8.6% across various sectors, including Electronics (7.5%), Non-ferrous Metals (7.4%), and Banking (7.3) [1] - The report tracks the performance of various strategies, noting that the S2 sentiment tracking strategy achieved a weekly excess return of 3.3%, while the S1 industry profitability tracking strategy underperformed with an excess return of -0.1% [2][3] - The report identifies the top-performing sectors for the week as Machinery (5.4%), Non-ferrous Metals (4.4%), and National Defense Industry (4.2%), while the worst performers were Oil & Petrochemicals (-0.9%), Pharmaceuticals (-0.9%), and Comprehensive Finance (-0.6%) [3][10] Industry Performance Review - The average weekly return for the 30 CITIC first-level industries was 1.9%, with a one-month average return of 4.2% [10] - The report provides a detailed breakdown of weekly and monthly performance for each industry, indicating significant variations in returns across sectors [11] Valuation Risk Warning - The report employs a valuation warning system based on the PB ratio over the past six years, identifying industries with a PB ratio above the 95th percentile as overvalued [12][13] - Currently, the industries triggering high valuation warnings include Retail Trade, National Defense Industry, and Media, all exceeding the 95% threshold [13][14] Strategy Performance - The report outlines the performance of various strategies, with the S4 long-term reversal strategy showing a significant excess return of 6.4% year-to-date [3][15] - The S3 macro style rotation strategy has a current excess return of 4.3%, indicating strong performance in the context of macroeconomic indicators [3][24] Sector Rankings - The report ranks the current high-prospect sectors based on profitability expectations, with Non-ferrous Metals, Communication, and Agriculture leading the rankings [16][19] - The sentiment tracking strategy (S2) identifies Machinery, Computer, and Textile as the top sectors based on implied sentiment indicators [19][20] Macro Indicators - The report highlights the top six industries favored by current macroeconomic indicators, which include Comprehensive Finance, Computer, Media, National Defense Industry, and Non-bank Financials [24][25]

Core Insights - The current industry allocation of the Bank of China multi-strategy system includes Computer (9.6%), Steel (9.2%), Non-ferrous Metals (7.8%), Consumer Services (7.2%), and Banking (6.8) among others, indicating a diversified investment approach across various sectors [1] - The average weekly return of the CITIC primary industries is 3.5%, with the best-performing sectors being Coal (10.5%), Steel (10.2%), and Non-ferrous Metals (9.6%), while the worst performers are Banking (-2.1%), Communication (-0.6%), and Comprehensive Finance (-0.1%) [3][11] - The composite strategy achieved a cumulative return of 3.4% this week, with an annual cumulative return of 16.4%, outperforming the CITIC primary industry equal-weight benchmark by 1.9% [3] - The highest weight strategy currently is the medium to long-term reversal strategy (S4) at 21.4%, while the lowest is the macro style rotation strategy (S3) at 8.0% [3] - Recent adjustments in positions indicate an increase in upstream cyclical sectors and a decrease in TMT sectors [3] Industry Performance Review - The top three industries in terms of weekly performance are Coal (10.5%), Steel (10.2%), and Non-ferrous Metals (9.6%), while the bottom three are Banking (-2.1%), Communication (-0.6%), and Comprehensive Finance (-0.1%) [11] - The average monthly return over the past month is 7.3%, indicating a positive trend across the industries [11] Valuation Risk Warning - The current PB valuation for the Retail, Automotive, Defense, and Media industries exceeds the 95th percentile of their historical valuations, triggering a high valuation warning [14][15] Strategy Performance - The S1 strategy focusing on high profitability industries shows a weekly excess return of -0.4%, while the S2 strategy tracking unverified sentiment has an excess return of 3.0% [3] - The S4 medium to long-term reversal strategy has the highest weight and has shown significant performance, indicating its effectiveness in the current market environment [3][16] Sector Rankings - The current top three sectors based on profitability expectations are Computer, Non-ferrous Metals, and Steel [17] - The S2 strategy ranks Mechanical, Computer, and Comprehensive as the top sectors based on implied sentiment [20] Macro Style Rotation - The macro style rotation strategy indicates a bullish outlook for Comprehensive Finance, Computer, Media, Defense, Electronics, and Comprehensive sectors based on current macro indicators [24][25]

Quantitative Models and Construction Methods Model 1: High Prosperity Industry Rotation Strategy (S1) - **Model Construction Idea**: The model aims to select industries with upward profit expectations by tracking industry profitability using a multi-factor model based on analysts' consensus expectations[16] - **Model Construction Process**: - Construct three major types of factors based on the original value, slope, and curvature of profit expectations - Screen candidate factors with annualized excess return >3% - Use hierarchical clustering to classify candidate factors into 8 categories and select the highest excess return factor from each category for rank equal-weighted composite - Exclude overvalued industries and select the top 3 industries with the highest factor values weekly[16] - **Model Evaluation**: The model effectively captures industries with high profitability expectations[16] Model 2: Implicit Sentiment Momentum Tracking Strategy (S2) - **Model Construction Idea**: The strategy constructs a sentiment momentum model that runs ahead of earnings expectation data by capturing "unproven sentiment" in the market[19] - **Model Construction Process**: - Perform cross-sectional regression of industry daily returns on daily turnover rate changes to strip out "expected sentiment" - Calculate the residual as "unproven sentiment" - Construct half-month and 12-month momentum factors based on cumulative unproven sentiment factor net value - Rank and equal-weight composite the two momentum factors - Exclude overvalued industries and select the top 3 industries with the highest factor values weekly[20] - **Model Evaluation**: The model captures market sentiment ahead of earnings expectation data[19] Model 3: Macro Style Rotation Strategy (S3) - **Model Construction Idea**: The strategy predicts the long-short situation of four industry styles (high beta, high valuation, 12-month momentum, high volatility) based on current macro indicators and their correlation with the returns of these styles[22] - **Model Construction Process**: - Construct a fundamental indicator system from "economic growth," "inflation," "currency," "credit," and "market sentiment" - Calculate the exposure of each industry to the four styles and estimate the expected long-short returns of the style factors - Use a weak voting classifier to predict the long-short of the styles - Map the style predictions to industries and select the top 6 industries with the highest total scores monthly[23] - **Model Evaluation**: The model effectively integrates macro indicators with industry style predictions[22] Model 4: Long-term Reversal Strategy (S4) - **Model Construction Idea**: The strategy leverages the momentum effect within 2 years and the reversal effect beyond 3 years in industries[27] - **Model Construction Process**: - Construct a "1-year momentum" factor excluding the most recent month's returns - Construct a "3-year reversal" factor using the period from 3 years ago to 2 years ago - Construct a turnover factor using the turnover rate of free float market value - Rank and equal-weight composite the three factors - Select the top 5 industries with the highest factor values monthly[27] - **Model Evaluation**: The model captures long-term reversal and medium-term momentum effects in industries[27] Model 5: Fund Flow Industry Rotation Strategy (S5) - **Model Construction Idea**: The strategy constructs an industry rotation model based on "market main fund flow and strength" and "late trading fund flow and strength"[29] - **Model Construction Process**: - Construct an "institutional order trend strength factor" using the net buy amount of institutional orders - Construct a "late trading fund flow and strength factor" using the average daily inflow of late trading funds - Rank and equal-weight composite the two factors - Select the top 5 industries with the highest fund inflow strength monthly[30] - **Model Evaluation**: The model effectively captures the flow and strength of market funds[29] Model 6: Financial Report Factor Failure Reversal Strategy (S6) - **Model Construction Idea**: The strategy leverages the phenomenon of financial report factors performing poorly in recent years to construct an industry rotation model based on the mean reversion theory of factor effectiveness[34] - **Model Construction Process**: - Classify financial report factors into categories and screen for "long-term effective factors" with annualized excess return >5.5% - Identify "short-term failure factors" that underperform the industry equal-weight benchmark for 4 consecutive months - Composite the highest annualized excess return factors from each category - Select the top 5 industries with the highest factor values monthly[35] - **Model Evaluation**: The model captures the mean reversion of financial report factors[34] Model 7: Multi-factor Scoring Composite Strategy (S7) - **Model Construction Idea**: The strategy is a quarterly rebalancing strategy that composites factors from "momentum," "liquidity," "valuation," and "quality" dimensions[39] - **Model Construction Process**: - Exclude industries with a weight below 2% in the CSI 800 - Select 2 factors from each dimension and rank equal-weight composite - Select the top 5 industries with the highest factor values quarterly[40] - **Model Evaluation**: The model effectively integrates multiple factor dimensions[39] Model Backtest Results - **S1**: Annualized excess return -1.8% YTD[66] - **S2**: Annualized excess return 5.6% YTD[66] - **S3**: Annualized excess return 2.7% YTD[66] - **S4**: Annualized excess return 4.8% YTD[66] - **S5**: Annualized excess return -0.2% YTD[66] - **S6**: Annualized excess return 0.6% YTD[66] - **S7**: Annualized excess return 3.9% YTD[66] - **Composite Strategy**: Annualized excess return 2.0% YTD[66]