Market Performance - The Shanghai Composite Index fell by 3.9% last week, closing at 3834.89 points, with a high of 3992.4 points [1] - The Shenzhen Component Index decreased by 5.13%, ending at 12538.07 points, with a peak of 13251.78 points [1] - The ChiNext Index dropped by 6.15%, closing at 2920.08 points, with a maximum of 3137.07 points [1] - Major global indices also declined, with the Nasdaq Composite down 2.74%, the Dow Jones Industrial Average down 1.91%, and the S&P 500 down 1.95% [1] - In the Asia-Pacific region, the Hang Seng Index fell by 5.09%, and the Nikkei 225 Index decreased by 3.48% [1] ETF Market Performance - The median weekly return for stock ETFs was -4.56% [2] - The highest weekly return among scale index ETFs was -2.17% for the CCB SSE 50 ETF [2] - The highest weekly return among industry index ETFs was -0.8% for the FTSE China 800 Bank ETF [2] - The highest weekly return among strategy index ETFs was -1.32% for the Harvest CSI 300 Dividend Low Volatility ETF [2] - The highest weekly return among theme index ETFs was -0.15% for the Penghua CSI Media ETF [2] ETF Liquidity and Fund Flows - Average daily trading volume for stock ETFs increased by 32.1%, and average daily turnover rose by 6.8% [6] - The top five stock ETFs with the highest fund inflows included the Huatai-PB CSI 300 ETF with an inflow of 3.876 billion yuan [8] - The top five stock ETFs with the highest fund outflows included the Hua Bao CSI Bank ETF with an outflow of 321 million yuan [8] Financing and Margin Trading - The financing balance for stock ETFs increased from 47.722 billion yuan to 50.553 billion yuan [9] - The highest financing buy amount was for the E Fund ChiNext ETF, totaling 801 million yuan [9] ETF Market Size and Composition - The total size of the ETF market reached 55,994.97 billion yuan, a decrease of 1,305.99 billion yuan from the previous week [13] - Stock ETFs accounted for 64.0% of the total ETF market size, with a total size of 35,817.94 billion yuan [15] - The number of stock ETFs in the market was 1,065 out of a total of 1,355 ETFs [10] New ETF Issuance - No new ETFs were issued last week, but eight new ETFs were established, including the Harvest Hang Seng Technology ETF and the Penghua Hang Seng Biotechnology ETF [16] Institutional Insights - Pacific Securities highlighted the importance of advancements in AI foundational model technology, particularly in e-commerce and advertising sectors [16] - Galaxy Securities noted the potential of AI video and social ecosystems, emphasizing the shift towards ecological construction and scene penetration in various industries [17]

Group 1: Macro Timing Strategy - The macro timing strategy has an annualized return of 7.67% as of October 31, 2025, with a Sharpe ratio of 1.45 and a Calmar ratio of 1.67, indicating a maximum drawdown of -4.60% [2][4][5] - The latest portfolio allocation includes 7.01% in CSI 300 ETF, 7.99% in CSI 500 ETF, 55.94% in government bond ETF, 11.63% in soybean meal ETF, 5.02% in non-ferrous ETF, 7.40% in gold ETF, and 5.00% in currency ETF, with no allocation to S&P 500 ETF and corporate bond ETF [7][8] Group 2: Momentum Strategy - The momentum strategy has an annualized return of 18.25% since January 2020, with a Sharpe ratio of 0.88 and a Calmar ratio of 0.64, experiencing a maximum drawdown of -28.72% [9][10] - The latest portfolio allocation includes 27.01% in Huatai-PB CSI Telecom Theme ETF, 24.92% in Fuguo CSI Tourism Theme ETF, 21.52% in Xinhua CSI Cloud Computing 50 ETF, 16.38% in Huatai-PB CSI Smart Car ETF, and 8.17% in Huaxia CSI Artificial Intelligence ETF [13][14] Group 3: Sector Rotation Strategy - The sector rotation strategy has an annualized return of 10.00% since 2020, with an excess return of 7.27% relative to CSI 300, and a maximum drawdown of -42.98% [15] - The latest portfolio includes home appliance ETF, green power ETF, steel ETF, new energy vehicle ETF, financial ETF, and agricultural ETF, while excluding non-ferrous metals ETF and transportation ETF [18][19] Group 4: Copula-Based Second-Order Stochastic Dominance Strategy - The Copula-based second-order stochastic dominance strategy has an annualized return of 14.41% since January 2020, with a Sharpe ratio of 0.68 and a maximum drawdown of -42.62% [20][24] - The latest portfolio allocation includes 5.00% in Huaxia CSI Petrochemical Industry ETF, 85.00% in Fuguo CSI 800 Bank ETF, 5.00% in Fuguo CSI All-Index Securities Company ETF, and 5.00% in Bosera CSI Oil and Gas Resources ETF [23][25] Group 5: Quantile Random Forest Technology ETF Allocation Strategy - The quantile random forest technology ETF allocation strategy has an annualized return of 13.54% since 2020, with a Sharpe ratio of 0.76 and a maximum drawdown of -29.89% [26] - The latest portfolio allocation consists of 95.63% in technology ETFs, including 4.78% in Jiahua National Communication ETF, 4.78% in Tianhong CSI Photovoltaic Industry ETF, 4.78% in Huabao CSI Military Industry ETF, 76.51% in Ping An CSI Consumer Electronics Theme ETF, and 4.78% in Fuguo CSI Technology 50 Strategy ETF [29][30]

Group 1: Report Overview - The report focuses on the construction methods and performance of various ETF portfolios in November 2025, including macro-based, macro + momentum, core - satellite, and trinity style rotation portfolios [2] Group 2: ETF Portfolio Construction Methods Based on Macro Approach - Calculate macro - sensitivity of indices tracked by broad - based, industry - themed, and Smart Beta ETFs according to economic, liquidity, and credit variables, and select ETFs monthly. Also consider adding momentum indicators. Traditional cyclical industries are suitable for economic up - periods, TMT for weak - economic but liquid - abundant times, and consumption benefits from credit expansion. Three ETF portfolios are constructed and rebalanced monthly [5] Trinity Style Rotation - Build a mid - to long - term style rotation model centered on macro - liquidity, compared with the CSI 300 index. Combine three models (growth/value, market - cap, and quality) to get 8 style preference results, then screen target - style - exposed ETFs with controlled industry exposure and set allocation limits [6] Group 3: Macro Industry Portfolio - Select industry - themed ETFs with over 1 - year establishment and over 200 million current scale. Calculate sensitivity scores, adjust according to economic, liquidity, and credit indicators, and select the top 6 industry - themed indices. Currently, with economic indicators rising and liquidity/credit tightening, the portfolio turns to value with high bank and cyclical proportions. November holdings are mainly bank and energy - related ETFs, each with a 16.67% weight. The portfolio has large fluctuations and was close to the CSI 300 in October [7][9][11] Group 4: Macro + Momentum Industry Portfolio - Combine macro and momentum methods to address the left - side bias of macro - based strategies. Use clustering to select one product with the highest 6 - month gain from each of 6 industry - themed groups. The portfolio includes many pro - cyclical industries. November holdings have multiple ETFs, with weights like 16.67% for some and 8.33% for others. The portfolio performed well this year and was close to the CSI 300 in October [12][14][15] Group 5: Core - Satellite Portfolio - Designed to address the high volatility and fast industry rotation of industry - themed ETFs. Use the CSI 300 as the core. Construct three sub - portfolios (broad - based, industry, and Smart Beta) and combine them at 50%, 30%, and 20% respectively. November holdings are mainly mid - to large - cap biased. The portfolio performed steadily this year, outperforming the index almost every month, including in October [16][17][21] Group 6: Trinity Style Rotation ETF Portfolio - The model favors small - cap growth + high - quality segments this period. The portfolio's factor exposure and historical performance are provided. November holdings include ETFs such as Southern CSI 500 ETF and Southern CSI 1000 ETF. The portfolio had significant fluctuations in monthly returns and outperformed the index in most months this year, including in October [22][23][26]

Market Overview - The Shanghai Composite Index increased by 1.67% to close at 3593.66 points, with a weekly high of 3613.02 points [1] - The Shenzhen Component Index rose by 2.33% to 11168.14 points, reaching a peak of 11210.91 points [1] - The ChiNext Index saw a 2.76% increase, closing at 2340.06 points, with a maximum of 2350.06 points [1] - Global markets also experienced gains, with the Nasdaq Composite up by 1.02%, the Dow Jones Industrial Average up by 1.26%, and the S&P 500 up by 1.46% [1] - In the Asia-Pacific region, the Hang Seng Index rose by 2.27%, and the Nikkei 225 increased by 4.11% [1] ETF Market Performance - The median weekly return for stock ETFs was 2.35% [2] - The highest weekly return among scale index ETFs was 23.12% for the Harvest SSE STAR Market Composite ETF [2] - The highest return in industry index ETFs was 9.74% for the China Tai SWS Coal ETF [2] - The top-performing strategy index ETF was the Fortune 500 Free Cash Flow ETF with a return of 4.22% [2] - The best-performing thematic index ETF was the ICBC Credit Suisse Rare Metals Theme ETF, which returned 11.8% [2] ETF Liquidity - Average daily trading volume for stock ETFs increased by 37.5%, while average daily turnover rose by 27.3% [7] ETF Fund Flows - The top five stock ETFs by inflow were: - GF Securities CSI Infrastructure Engineering ETF with an inflow of 321 million yuan - E Fund CSI Artificial Intelligence Theme ETF with 305 million yuan - Bosera SSE STAR Market Artificial Intelligence ETF with 260 million yuan - E Fund National Robot Industry ETF with 225 million yuan - Southern S&P China A-share Large Cap Dividend Low Volatility 50 ETF with 211 million yuan [9] - The top five stock ETFs by outflow were: - Huaxia SSE STAR Market 50 Component ETF with an outflow of 823 million yuan - Huaxia CSI A500 ETF with 465 million yuan - Southern CSI 1000 ETF with 438 million yuan - Invesco Great Wall CSI A500 ETF with 420 million yuan - Huaxia SSE 50 ETF with 365 million yuan [10] ETF Financing and Margin Trading - The financing balance for stock ETFs decreased from 41.0568 billion yuan to 40.6035 billion yuan [12] - The highest financing buy amount was for the Huaxia SSE STAR Market 50 Component ETF, totaling 855 million yuan [12] ETF Market Size - The total market size for ETFs reached 46,278.58 billion yuan, an increase of 881.93 million yuan from the previous week [15] - Stock ETFs accounted for 31,670.36 billion yuan, representing the largest category in the ETF market [15] Institutional Perspectives - Galaxy Securities expressed optimism about the bank sector's allocation value, highlighting the benefits from ETF quality enhancement and the accumulation of positive fundamental factors [19] - Huachuang Securities emphasized the importance of bank sector allocation opportunities, noting an increase in overall positions and the potential for additional funds due to long-term capital inflows and public fund reforms [20]

Market Performance - The recent five trading days saw the Sci-Tech 50 Index decline by 0.36%, the ChiNext Index by 1.40%, and the large-cap value index by 0.16%, while the large-cap growth index fell by 2.71%. The Shanghai 50 Index decreased by 1.22%, whereas the small-cap index represented by the CSI 2000 rose by 0.94%. Sectors such as environmental protection and biomedicine performed well, while automotive and electrical equipment lagged behind [1]. Risk Premium Analysis - The risk premium, defined as the inverse of the static PE of the CSI All Index (EP) minus the yield of ten-year government bonds, indicates that the implied returns of equity and bond assets are at historically significant levels. For instance, on April 26, 2022, the risk premium reached 4.17%, and on October 28, 2022, it was 4.08%. As of January 19, 2024, the indicator stood at 4.11%, marking the fifth occurrence since 2016 of exceeding 4%. As of May 30, 2025, the indicator was at 3.90%, with the two-standard deviation boundary set at 4.75% [1]. Valuation Levels - As of May 30, 2025, the CSI All Index's PETTM was at the 50th percentile, with the Shanghai 50 and CSI 300 at 61% and 48%, respectively. The ChiNext Index was close to 11%, while the CSI 500 and CSI 1000 were at 30% and 32%. The ChiNext Index's valuation style is relatively low compared to historical averages [2]. Long-term Market Trends - The technical analysis of the Deep 100 Index indicates a cyclical pattern of bear markets every three years, followed by bull markets. Historical declines ranged from 40% to 45%, with the current adjustment starting in the first quarter of 2021 showing sufficient time and space for a potential upward cycle [2]. Fund Flow and Trading Activity - In the last five trading days, ETF inflows totaled 8.5 billion yuan, with margin trading increasing by approximately 720 million yuan. The average daily trading volume across both markets was 10.687 billion yuan [4]. AI and Machine Learning Applications - The use of convolutional neural networks (CNN) for modeling price and volume data has been explored, with features mapped to industry themes. The latest focus is on sectors such as banking [3][10].

Market Performance - The Sci-Tech 50 Index decreased by 1.47% over the last five trading days, while the ChiNext Index fell by 0.88%. In contrast, the large-cap value stocks rose by 0.48%, and the large-cap growth stocks declined by 0.40% [1] - The medical and biological sectors performed well, while the computer and machinery equipment sectors lagged behind [1] Risk Premium Analysis - The static PE of the CSI All Share Index minus the yield of 10-year government bonds indicates a risk premium. Historical extreme bottoms have shown this data to be at two standard deviations above the mean, with recent peaks at 4.17% on April 26, 2022, and 4.11% on January 19, 2024. As of May 23, 2025, the indicator stands at 3.84%, with the two standard deviation boundary at 4.76% [1] Valuation Levels - As of May 23, 2025, the CSI All Share Index's TTM PE is at the 51st percentile, with the SSE 50 and CSI 300 at 62% and 49%, respectively. The ChiNext Index is close to 11%, indicating a relatively low valuation level compared to historical averages [2] Long-term Market Trends - The Shenzhen 100 Index has experienced bear markets approximately every three years, followed by bull markets. The current adjustment, which began in Q1 2021, has shown sufficient time and space for a potential upward cycle [2] Fund Flow and Trading Activity - In the last five trading days, ETF funds saw an outflow of 24 billion yuan, while margin financing decreased by approximately 20 million yuan. The average daily trading volume across both markets was 1.1376 trillion yuan [3] AI and Machine Learning Applications - A convolutional neural network (CNN) has been utilized to model price and volume data, mapping learned features to industry themes. The latest focus is on sectors such as banking and dividends [2][10]

Group 1 - The financial sector has shown strong performance recently, with the Wind banking industry index reaching a historical high of 7072.61 points as of May 15, contributing to a positive market sentiment [1][2] - The A-share Wind non-bank financial sector has seen an increase of nearly 4% this week, while the Wind banking sector rose by 2.1% [2] - Several financial stocks, including China Pacific Insurance and Hongta Securities, hit the daily limit, and multiple bank stocks reached historical highs [2] Group 2 - Analysts believe that the recent rally in banks, insurance, and securities is driven by three main factors: the continuous decline in risk-free interest rates, ongoing regulatory reforms, and increased insurance capital investments [3] - The public fund reform is expected to lead to a significant inflow of funds into the banking and non-bank financial sectors, as current allocations are below benchmark indices [4] - The anticipated influx of capital is supported by the recent approval of 600 billion yuan for long-term insurance investments and adjustments in risk factors for stock investments [4] Group 3 - The stable growth orientation and continued fiscal policy support are expected to improve the banking operating environment, further supporting the sector's fundamentals [4] - The recent capital increases by major state-owned banks, exceeding 500 billion yuan, signal stability in the financial system and may enhance investor confidence [4]

Core Viewpoint - The banking sector in A-shares has reached a historic high with a total market capitalization surpassing 10 trillion yuan, driven by a series of monetary easing policies from the central bank, leading to increased investor interest and stock price surges in various banks [1][5]. Group 1: Market Performance - Major banks such as Industrial and Commercial Bank of China (ICBC) and Agricultural Bank of China have seen significant market capitalizations of 1.95 trillion yuan and 1.8 trillion yuan respectively, contributing to the overall growth of the banking sector [1]. - The banking sector index has shown a strong performance, with a 3-day consecutive increase and an 8.71% rise over the past 20 trading days, placing it among the top-performing sectors [1][2]. Group 2: Institutional Investment - Institutional funds, including insurance capital and central Huijin, have increasingly invested in the banking sector, with central Huijin heavily investing in eight major bank stocks, indicating a shift towards seeking stable returns [2][5]. - The net inflow of northbound funds into the banking sector exceeded 50 billion yuan in the first quarter of 2025, highlighting the sector's appeal during market downturns [5]. Group 3: Investment Attractiveness - The banking sector is characterized by low valuations, with an average price-to-book (PB) ratio of approximately 0.6, indicating a high margin of safety for investors [3]. - High dividend yields, with major banks like ICBC and China Construction Bank offering yields over 5%, make the sector attractive for income-seeking investors [4]. - The banking sector benefits from strong policy support and stable fundamentals, particularly under the current favorable monetary policies, which are expected to enhance profitability and asset quality [5]. Group 4: ETF Options - The market offers various banking ETFs, including the comprehensive CSI Bank Index ETF, which includes all listed banks, providing a diversified investment option [6]. - The CSI Bank AH Price Selection Index focuses on banks listed in both A and H shares, allowing for cross-market arbitrage opportunities [7]. - The CSI 800 Bank Index selects top-performing banks, providing a more concentrated investment strategy [8]. Group 5: Valuation Insights - Research indicates that the banking sector remains undervalued, with PB and PE ratios ranking among the lowest across industries, suggesting potential for upward correction in valuations [11].

Market Performance - The recent 5 trading days saw the Sci-Tech 50 Index increase by 0.24%, the ChiNext Index rise by 4.13%, large-cap value stocks up by 1.55%, large-cap growth stocks up by 2.05%, the SSE 50 Index up by 1.46%, and the small-cap represented by the CSI 2000 up by 3.77% [1] - The defense and military industry, as well as the communication sector, performed well, while steel and retail sectors lagged behind [1] Risk Premium Analysis - The static PE of the CSI All Index minus the yield of 10-year government bonds indicates a risk premium, which has historically reached extreme levels at two standard deviations above the mean during significant market bottoms, such as in 2012, 2018, and 2020 [1] - As of April 26, 2022, the risk premium reached 4.17%, and on October 28, 2022, it was 4.08%, with a recent reading of 4.11% on January 19, 2024, marking the fifth occurrence since 2016 of exceeding 4% [1] Valuation Levels - As of May 9, 2025, the CSI All Index's PETTM is at the 50th percentile, with the SSE 50 and CSI 300 at 61% and 47% respectively, while the ChiNext Index is close to 11% [2] - The ChiNext Index's valuation is relatively low compared to historical averages [2] Long-term Market Trends - The technical analysis of the Deep 100 Index indicates a pattern of bear markets every three years followed by bull markets, with previous declines ranging from 40% to 45% [2] - The current adjustment cycle began in Q1 2021, suggesting a potential for upward movement from the bottom [2] Fund Flow and Trading Activity - In the last 5 trading days, ETF funds saw an outflow of 17.9 billion yuan, while margin trading increased by approximately 4.4 billion yuan [2] - The average daily trading volume across both markets was 1.2918 trillion yuan [2] AI and Machine Learning Insights - A convolutional neural network (CNN) was utilized to model price and volume data, mapping learned features to industry themes, with a current focus on banking [2][7] Market Sentiment - The proportion of stocks above the 200-day moving average is being tracked to gauge market sentiment [9] Equity and Bond Risk Preference - Ongoing monitoring of risk preferences between equity and bond assets is being conducted [11]

Core Viewpoint - CITIC Securities has made significant adjustments to its ETF holdings, increasing positions in certain ETFs while reducing others, indicating a strategic shift in investment focus towards specific sectors and market segments [1][9]. Group 1: ETF Holdings Overview - CITIC Securities holds the largest position in the Huaxia SSE 50 ETF with a market value of 2 billion yuan, despite a reduction of 50.91 million shares [2][3]. - The second largest holding is the Huaxia CSI A500 ETF, valued at 1.846 billion yuan, reflecting a stable investment strategy as no changes in holdings were reported [2][3]. - The Southern CSI 1000 ETF has seen an increase of 25.51 million shares, indicating a focus on small-cap stocks, which are expected to perform well in the current market environment [2][4]. Group 2: Increases in Holdings - The Southern CSI 1000 ETF was increased by 255 million shares, highlighting CITIC Securities' positive outlook on small-cap stocks and emerging industries [4][5]. - The Tianhong CSI Bank ETF was increased by 6.534 million shares, reflecting confidence in the banking sector amid a favorable macroeconomic environment [5][6]. - The E-Fund SSE 50 ETF saw an increase of 4.492 million shares, emphasizing the importance of large-cap blue-chip stocks in the investment strategy [5][6]. Group 3: Reductions in Holdings - CITIC Securities reduced its holdings in the Southern CSI 500 ETF by 860 million shares, indicating caution towards mid-cap stocks due to potential market uncertainties [7][8]. - The Huaxia SSE 50 ETF also experienced a reduction of 509 million shares, suggesting a strategic shift in focus away from large-cap stocks [7][8]. - The Southern MSCI China A50 ETF was reduced by 261 million shares, further reflecting a cautious approach to blue-chip stocks in the current market context [7][8]. Group 4: New Entrants and Exits - CITIC Securities entered the top ten holders of 46 new non-cash ETFs, indicating a diversification strategy to capture various market opportunities [9][10]. - The firm exited the top ten holders of the Hai Fu Tong SSE Urban Investment Bond ETF, Southern CSI 300 ETF, and the China Merchants CSI Dividend ETF, marking a significant portfolio adjustment [14][15].