Group 1 - The report indicates that in the last month, equities, commodities, and bonds all experienced increases, with equities and commodities rising by 2.50% and 4.03% respectively, while gold decreased by 0.57% [2][10] - The performance of ETFs used in the allocation strategy showed that the CSI 300 ETF, non-ferrous ETF, and energy chemical ETF increased by 2.85%, 3.08%, and 4.37% respectively, while the gold ETF saw a significant decline of 0.75% [2][13] Group 2 - The backtested strategy from January 1, 2014, to the end of last month achieved an annualized return of 7.71%, with an annualized volatility of 3.53% and a maximum drawdown of 3.17%. The Sharpe ratio and Calmar ratio were 2.19 and 2.44 respectively, outperforming risk parity and equal-weighted strategies [3][25] - The strategy without currency assets yielded a return of 0.48% last month, which was lower than both the risk parity strategy and the equal-weighted strategy [3][28] Group 3 - The latest allocation recommendations suggest increasing exposure to equities and commodities, while maintaining a neutral position on bonds and gold. The final weights for equities, government bonds, commodities, and gold are set at 7.01%, 75.01%, 10.90%, and 7.08% respectively [4][32]

1. Report Industry Investment Rating - Not provided in the content 2. Core Viewpoints of the Report - This week, the A-share market rebounded strongly, with the Shanghai Composite Index breaking through the year's high. The average daily trading volume increased by 22.36% week-on-week. The market risk appetite increased due to the easing geopolitical situation and the introduction of domestic growth-stabilizing policies [1][10]. - The financial technology sector led the rise this week, with both financial and growth styles performing well. The growth style index rose 5.21% this week, and its trading volume accounted for 54.20% of the total, reaching a four-week high [14]. - Looking ahead, the market is expected to maintain a steady upward trend. In July, the market is expected to see an orderly rotation of hot sectors. However, investors should remain cautious before the uncertainties of Sino-US tariff negotiations and the Fed's interest rate decision are eliminated [15]. 3. Summary According to the Directory 3.1 This Week's Market Review 3.1.1 Industry Index - The comprehensive finance, computer, comprehensive, national defense and military industry, and non-bank finance sectors led the gains this week. The trading volume of non-bank finance and bank sectors increased significantly compared to last week, while the trading activity of media, petroleum and petrochemical, medicine, food and beverage, and agriculture, forestry, animal husbandry, and fishery sectors decreased significantly [10]. - COMEX gold fell 2.94%, and the Chinese bond market maintained a narrow range of fluctuations. The basis of stock index futures contracts increased overall, and the net value of stock hedging strategies continued to decline. The average and median returns of neutral hedging funds this week were -0.10% and -0.03% respectively [1][10]. 3.1.2 Market Style - The financial technology sector led the rise this week, driving the market index higher. The growth style index rose 5.21% this week, and its trading volume accounted for 54.20% of the total, reaching a four-week high. The consumer style index rose 1.46%, and its trading volume accounted for 10.93% of the total, reaching a four-week low [14]. - The financial style index rose 3.41%, and its trading volume accounted for 10.07% of the total, reaching a four-week high. The stable style index rose only 0.78%, and its trading volume accounted for 3.45% of the total, reaching a four-week low [14]. - The cyclical style index rose 3.02%, and its trading volume accounted for 21.35% of the total, reaching a four-week low. The CSI 2000 index rose 5.55% this week, but its trading volume accounted for 28.89% of the total, reaching a four-week low [14]. 3.2 Active Equity Funds 3.2.1 Funds with Excellent Performance in Different Theme Tracks This Week - In the single-track fund category, the top five funds in terms of performance this week were Dongcai Value Qihang A, Taixin Development Theme, Chang'an Yusheng A, Huashang Upstream Industry A, and Huitianfu Consumption Upgrade A [20]. - In the double-track fund category, the top five funds in terms of performance this week were China Merchants Securities Technology Theme 6-Month Holding A, Yin Hua Multi-Power, Yongying High-End Equipment Smart Selection A, Huashang Computer Industry Quantitative A, and Hongtu Innovation Selection LOF [20]. 3.2.2 Funds with Excellent Performance in Different Strategy Categories - In the deep undervaluation strategy, the top three funds were Orient Internet Jia, Qianhai Kaiyuan Event-Driven A, and GF Shanghai-Hong Kong-Shenzhen Value Growth A [2][22]. - In the high-growth strategy, the top three funds were China Europe Prosperity Outlook One-Year Holding A, Yuanxin Yongfeng High-End Manufacturing, and Huafu Guotai Min'an A [2][22]. - In the high-quality strategy, the top three funds were Furong Fujin A, Great Wall Jiuxin A, and E Fund New Normal [2][22]. - In the quality undervaluation strategy, the top three funds were Tongtai Financial Selection A, Qianhai Kaiyuan Shengxin A, and Wells Fargo Financial Real Estate Industry A [2][22]. - In the quality growth strategy, the top three funds were AVIC New Takeoff A, SDIC UBS New Energy A, and E Fund National Defense and Military Industry A [2][22]. - In the GARP strategy, the top three funds were Guoshou Anbao Target Strategy A, Guotai Dazhizao Two-Year Holding, and China AMC Panyi One-Year Fixed Open [2][22]. - In the balanced cost-performance strategy, the top three funds were Hongtu Innovation Selection LOF, Chang Sheng State-Owned Enterprise Reform Theme, and Taixin Development Theme [2][22]. 3.3 Index Enhanced Funds 3.3.1 This Week's Excess Return Distribution of Index Enhanced Funds - The average and median excess returns of CSI 300 index enhanced funds were 0.06% and 0.10% respectively [25]. - The average and median excess returns of CSI 500 index enhanced funds were -0.35% and -0.37% respectively [25]. - The average and median excess returns of CSI 1000 index enhanced funds were -0.20% and -0.22% respectively [25]. - The average and median excess returns of CSI 2000 index enhanced funds were -0.04% and -0.06% respectively [25]. - The average and median excess returns of CSI A500 index enhanced funds were 0.11% and 0.13% respectively [25]. - The average and median excess returns of ChiNext index enhanced funds were -0.20% and -0.17% respectively [25]. - The average and median excess returns of STAR Market and ChiNext 50 index enhanced funds were -0.11% and -0.14% respectively [26]. 3.4 This Issue's Bond Fund Selections - The report screened out the medium- and long-term bond fund pool and the short-term bond fund pool based on indicators such as fund size, performance risk indicators, the latest fund size, Wind Fund secondary classification, three-year rolling returns, and three-year maximum drawdowns [42]. 3.5 This Week's High-Frequency Fund Position Detection - Active equity funds significantly increased their positions in the petroleum and petrochemical (0.18%), coal (0.09%), and comprehensive (0.08%) industries this week; they significantly reduced their positions in the machinery (0.19%), automobile (0.13%), and commercial and retail (0.08%) industries [3]. - From a one-month perspective, the position of the pharmaceutical industry increased significantly by 0.71%, while the positions of the machinery and automobile industries decreased significantly by 0.64% and 0.65% respectively [3]. 3.6 This Week's Weekly Tracking of US Dollar Bond Funds - Not provided in the content

Quantitative Models and Construction Methods Model 1: RSI (Relative Strength Index) - **Model Name**: RSI (Relative Strength Index) - **Model Construction Idea**: The RSI is used to measure the speed and change of price movements. It is primarily used to identify overbought or oversold conditions in a trading instrument. - **Model Construction Process**: - The RSI is calculated using the following formula: $$ RSI = 100 - \frac{100}{1 + RS} $$ where RS (Relative Strength) is the average of 'n' days' up closes divided by the average of 'n' days' down closes. Typically, a 14-day period is used. - The RSI value ranges from 0 to 100. An RSI above 70 indicates that the market is overbought, while an RSI below 30 indicates that the market is oversold.[2] Model 2: Net Purchase (NETBUY) - **Model Name**: Net Purchase (NETBUY) - **Model Construction Idea**: This model calculates the net purchase amount of an ETF to understand the inflow and outflow of funds. - **Model Construction Process**: - The net purchase amount is calculated using the following formula: $$ NETBUY(T) = NAV(T) - NAV(T-1) \times (1 + R(T)) $$ where NETBUY(T) is the net purchase amount on day T, NAV(T) is the net asset value on day T, NAV(T-1) is the net asset value on the previous trading day, and R(T) is the return on day T.[2] Model Backtesting Results - **RSI Model**: - RSI values for various ETFs range from 37.69 to 80.86, indicating different levels of market conditions from oversold to overbought.[4][6] - **Net Purchase Model**: - Net purchase values for various ETFs range from -6.38 billion to 99.72 billion, indicating significant variations in fund inflows and outflows.[4][6] Quantitative Factors and Construction Methods Factor 1: Institutional Holdings - **Factor Name**: Institutional Holdings - **Factor Construction Idea**: This factor measures the percentage of an ETF's holdings that are owned by institutional investors. - **Factor Construction Process**: - The percentage of institutional holdings is derived from the latest annual or semi-annual reports of the ETF, excluding the holdings of corresponding linked funds. The data is an estimate and may have some deviations.[3] Factor Backtesting Results - **Institutional Holdings Factor**: - Institutional holdings percentages for various ETFs range from 2.79% to 96.29%, indicating varying levels of institutional interest and confidence in these ETFs.[4][6]

Market Liquidity Overview - R007 increased from 1.5811% to 1.591%, a rise of 0.99 basis points, while DR007 decreased from 1.502% to 1.4941%, a drop of 0.79 basis points. The spread between R007 and DR007 widened by 1.78 basis points [9][11] - The net outflow of funds this week was 320.904 billion, an increase of 391.818 billion from the previous week. Fund supply was 144.097 billion, and fund demand was 465.001 billion [11][12] Industry Sector Liquidity Tracking - Most sectors in the CITIC first-level industry recorded declines, with the banking sector showing the strongest performance, up 3.13%. The pharmaceutical and textile sectors led the declines, falling 4.16% and 4.10% respectively [16][17] - The pharmaceutical industry had the highest overall congestion score, indicating significant market activity and potential risk [27][28] Style Sector Liquidity Tracking - The consumer style index experienced the largest decline of 3.90%, while the financial style saw a slight increase of 0.05%, making it the only sector with positive returns [32][33] - The growth style maintained the highest daily trading volume share at 52.43%, significantly ahead of other styles, and also had the highest turnover rate at 2.33% [30][32]

证券研究报告—ETF 基金周报 撰写日期：2025 年 06 月 23 日 ETF 周报（20250616-20250620） 摘要 ETF 新发及上市情况： 在样本期内一共有 10 只基金成立，6 只基金上 市。 风险提示：本报告对于基金产品、指数的研究分析均基于历史公开信 息，可能受指数样本股的变化而产生一定的分析偏差；此外，基金管理人的 历史业绩与表现不代表未来；指数未来表现受宏观环境、市场波动、风格转 换等多重因素影响，存在波动风险；本报告不涉及证券投资基金评价业务， 不涉及对基金产品的推荐，亦不涉及对任何指数样本股的推荐。 麦高证券 研究发展部 分析师：林永绿 资格证书：S0650524060001 联系邮箱：linyonglv@mgzq.com 联系电话：15000307034 联系人：张昊阳 资格证书：S0650124040024 联系邮箱：zhanghaoyang@mgzq.com 联系电话：13363378283 相关研究 《麦高视野--ETF 观察日志（20250620）》 2025.06.23 《麦高视野--ETF 观察日志（20250619）》 2025.06.20 《麦高视野--ET ...

ETF Performance Overview - The Huatai-PB CSI 300 ETF has a market value of CNY 368.77 billion and a decline of 0.79% with an RSI of 30.88, indicating a near oversold condition[4] - The E Fund CSI 300 ETF also shows a decline of 0.79% with a market value of CNY 260.36 billion and an RSI of 45.05, suggesting moderate market strength[4] - The CSI 500 ETFs, such as the Southern CSI 500 ETF, have experienced a decline of 1.00% with a market value of CNY 109.87 billion and an RSI of 44.88, indicating a weak market[4] Market Trends and Indicators - The overall market sentiment is reflected in the RSI values, with several ETFs showing RSI below 30, indicating oversold conditions, such as the Tianhong CSI 300 ETF with an RSI of 45.32[4] - Net purchases for the Huatai-PB CSI 300 ETF were negative at CNY -5.49 billion, indicating a trend of selling pressure[4] - The trading volume for the Huatai-PB CSI 300 ETF was CNY 23.31 billion, reflecting active trading despite the price decline[4] Sector-Specific Insights - The Consumer Electronics sector ETFs, such as the Huaxia National Index Consumer Electronics ETF, have shown a decline of 0.63% with an RSI of 55.27, indicating a relatively stable market[6] - The Non-Bank sector ETFs, including the E Fund Non-Bank ETF, have experienced a decline of 1.66% with an RSI of 47.50, suggesting a cautious outlook[6] - The New Energy sector ETFs, like the Southern CSI New Energy ETF, have shown a decline of 1.16% with an RSI of 44.37, indicating potential weakness in this sector[6]

Group 1: Financial Data Overview - In May 2025, the total social financing increased by 22,894 billion yuan, which is 2,271 billion yuan more than the same period last year[2] - The stock growth rate of social financing recorded 8.7%, remaining unchanged from the previous value[2] - New RMB loans in May amounted to 6,200 billion yuan, which was lower than expected, indicating a need for improved effective financing demand[2] Group 2: Government Financing and Loan Trends - Government bonds increased by 14,633 billion yuan in May, reflecting a year-on-year increase of 2,367 billion yuan, supporting social financing expansion[9] - Corporate loans increased by 5,300 billion yuan, but this was a year-on-year decrease of 2,100 billion yuan, influenced by global trade tensions[10] - Resident loans increased by 540 billion yuan, but this also represented a year-on-year decrease of 217 billion yuan, showing weak leverage willingness post-interest rate cuts[10] Group 3: Monetary Supply and Policy Implications - M2 growth rate in May recorded 7.9%, a slight decrease of 0.1 percentage points from the previous month, likely due to slowed credit expansion[14] - M1 growth rate improved by 0.8 percentage points to 2.3%, reflecting the impact of recent financial support policies on market confidence[14] - Future strategies should focus on enhancing fiscal efforts and coordinating monetary policy to stimulate financing willingness in the real economy[19] Group 4: Risks and Challenges - Risks include potential underperformance of policy implementation, slower-than-expected economic recovery, and unexpected developments in US-China trade tensions[21]

证券研究报告—策略周报 撰写日期：2025 年 06 月 16 日 策略周报（20250609-20250613） ⚫ 市场流动性概况 R007 由 1.5514%增加至 1.5811% ，较前期增加了 2.97 个 bp；DR007 由 1.5323%下降至 1.502%，较前值减少了 3.03 个 bp。R007 与 DR007 利差 较前期增加了 6.00 个 bp。此外，中美利差在本周减少了 8.19 个 bp。 本周资金净流入金额为 709.14 亿元，较上周增加了 142.27 亿元， 其中资金供给为 1323.94 亿元，资金需求为 614.80 亿元。具体来看，资 金供给增加了 480.21 亿元，其中融资净买入增加了 8.43 亿元，股票分红 增加了 653.35 亿元，股票型 ETF 净申赎减少了 61.95 亿元,股票型基金与 混合型基金成立减少了 119.62 亿元；资金需求增加了 337.94 亿元。 ⚫ 行业板块流动性跟踪 本周中信一级行业涨跌互现，市场风格分化明显，涨跌行业数量大致 相当。从上涨板块来看，有色金属和石油石化领涨，分别上涨约 3.95%和 3.31%。下跌方面，食品 ...

证券研究报告—ETF 基金周报 撰写日期：2025 年 06 月 16 日 ETF 周报（20250609-20250613） 摘要 二级市场概况：统计 A 股、海外主要宽基指数、黄金指数和南华商 品指数的走势，样本期内南华商品指数、SGE 黄金 9999 和恒生指数本周收 益排名靠前，分别为 2.14%、1.56%和 0.42%。计算所有申万一级行业在样本 期内的收益情况，其中有色金属、石油石化和农林牧渔的收益排名靠前，分 别为 3.79%、3.50%和 1.62%，食品饮料、家用电器和建筑材料的收益排名较 为靠后，分别为-4.37%、-3.26%和-2.77%。 ETF 资金流情况：从不同类别 ETF 角度来看，债券 ETF 的资金净流入 最多，为 143.91 亿元；宽基 ETF 的资金净流入最少，为-106.32 亿元。从 ETF 跟踪指数及其成分股上市板块角度来看，港股 ETF 的资金净流入最多， 为 42.32 亿元；创业板相关 ETF 的资金净流入最少，为-34.04 亿元。从行 业板块角度来看，周期板块 ETF 的资金净流入最多，为 7.86 亿元；生物医 药板块 ETF 的资金净流入最少，为 ...

Quantitative Models and Construction Methods Model Name: RSI (Relative Strength Index) - Construction Idea: RSI measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset[2] - Detailed Construction Process: - Calculate the average gain and average loss over a specified period (12 days) - Use the formula: $ RSI = 100 - 100 / (1 + RS) $ where RS is the average gain divided by the average loss[2] - Evaluation: RSI > 70 indicates the market is in an overbought condition, while RSI < 30 indicates the market is in an oversold condition[2] Model Name: NETBUY (Net Purchase Amount) - Construction Idea: NETBUY calculates the net purchase amount of an ETF based on its net asset value (NAV) and return[2] - Detailed Construction Process: - Use the formula: $ NETBUY(T) = NAV(T) - NAV(T-1) * (1 + R(T)) $ where NETBUY(T) is the net purchase amount, NAV(T) is the net asset value on day T, NAV(T-1) is the net asset value on the previous trading day, and R(T) is the return on day T[2] Model Backtesting Results - RSI Model, RSI values for various ETFs: - Huatai-PB CSI 300 ETF: 59.63[4] - E Fund CSI 300 ETF: 59.08[4] - ChinaAMC CSI 300 ETF: 59.30[4] - Harvest CSI 300 ETF: 58.93[4] - Tianhong CSI 300 ETF: 58.51[4] - Southern CSI 500 ETF: 61.53[4] - ChinaAMC CSI 500 ETF: 61.49[4] - Harvest CSI 500 ETF: 60.75[4] - E Fund CSI 500 ETF: 61.56[4] - ChinaAMC SSE 50 ETF: 52.77[4] - E Fund SSE 50 ETF: 54.31[4] - CCB SSE 50 ETF: 50.97[4] - Huatai-PB CSI 2000 ETF: 61.30[4] - Southern CSI 2000 ETF: 62.21[4] - ChinaAMC CSI 2000 ETF: 64.83[4] - Ping An CSI A50 ETF: 52.58[4] - Dacheng CSI A50 ETF: 53.33[4] - E Fund CSI A50 ETF: 53.38[4] - ChinaAMC CSI A100 ETF: 54.52[4] - GF CSI A100 ETF: 53.52[4] - Guotai CSI A500 ETF: 58.13[4] - Southern CSI A500 ETF: 58.98[4] - GF CSI A500 ETF: 58.87[4] - ChinaAMC SSE STAR 50 ETF: 40.85[4] - E Fund SSE STAR 50 ETF: 41.06[4] - ICBC SSE STAR 50 ETF: 41.47[4] - Bosera SSE STAR 100 ETF: 56.52[4] - Penghua SSE STAR 100 ETF: 56.74[4] - ChinaAMC SSE STAR 100 ETF: 57.03[4] - E Fund GEM ETF: 59.93[4] - Tianhong GEM ETF: 59.90[4] - GF GEM ETF: 60.01[4] - ChinaAMC Hang Seng Tech ETF: 54.81[4] - ChinaAMC Hang Seng ETF: 63.75[4] - ChinaAMC HK-Hang Seng ETF: 63.63[4] - Huaan Mitsubishi UFJ Nikkei 225 ETF: 63.21[4] - ChinaAMC Nomura Nikkei 225 ETF: 62.65[4] - GF Nasdaq 100 ETF: 59.68[4] - Guotai Nasdaq 100 ETF: 60.09[4] - Bosera S&P 500 ETF: 63.67[4] - Penghua Dow Jones Industrial Average ETF: 58.87[4] - Huatai-PB Southern East Asia Saudi Arabia ETF: 44.60[4] - Huaan Germany (DAX) ETF: 51.84[4] - Huaan France CAC40 ETF: 56.31[4] Quantitative Factors and Construction Methods Factor Name: RSI (Relative Strength Index) - Construction Idea: RSI measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset[2] - Detailed Construction Process: - Calculate the average gain and average loss over a specified period (12 days) - Use the formula: $ RSI = 100 - 100 / (1 + RS) $ where RS is the average gain divided by the average loss[2] - Evaluation: RSI > 70 indicates the market is in an overbought condition, while RSI < 30 indicates the market is in an oversold condition[2] Factor Name: NETBUY (Net Purchase Amount) - Construction Idea: NETBUY calculates the net purchase amount of an ETF based on its net asset value (NAV) and return[2] - Detailed Construction Process: - Use the formula: $ NETBUY(T) = NAV(T) - NAV(T-1) * (1 + R(T)) $ where NETBUY(T) is the net purchase amount, NAV(T) is the net asset value on day T, NAV(T-1) is the net asset value on the previous trading day, and R(T) is the return on day T[2] Factor Backtesting Results - RSI Factor, RSI values for various ETFs: - Huatai-PB CSI 300 ETF: 59.63[4] - E Fund CSI 300 ETF: 59.08[4] - ChinaAMC CSI 300 ETF: 59.30[4] - Harvest CSI 300 ETF: 58.93[4] - Tianhong CSI 300 ETF: 58.51[4] - Southern CSI 500 ETF: 61.53[4] - ChinaAMC CSI 500 ETF: 61.49[4] - Harvest CSI 500 ETF: 60.75[4] - E Fund CSI 500 ETF: 61.56[4] - ChinaAMC SSE 50 ETF: 52.77[4] - E Fund SSE 50 ETF: 54.31[4] - CCB SSE 50 ETF: 50.97[4] - Huatai-PB CSI 2000 ETF: 61.30[4] - Southern CSI 2000 ETF: 62.21[4] - ChinaAMC CSI 2000 ETF: 64.83[4] - Ping An CSI A50 ETF: 52.58[4] - Dacheng CSI A50 ETF: 53.33[4] - E Fund CSI A50 ETF: 53.38[4] - ChinaAMC CSI A100 ETF: 54.52[4] - GF CSI A100 ETF: 53.52[4] - Guotai CSI A500 ETF: 58.13[4] - Southern CSI A500 ETF: 58.98[4] - GF CSI A500 ETF: 58.87[4] - ChinaAMC SSE STAR 50 ETF: 40.85[4] - E Fund SSE STAR 50 ETF: 41.06[4] - ICBC SSE STAR 50 ETF: 41.47[4] - Bosera SSE STAR 100 ETF: 56.52[4] - Penghua SSE STAR 100 ETF: 56.74[4] - ChinaAMC SSE STAR 100 ETF: 57.03[4] - E Fund GEM ETF: 59.93[4] - Tianhong GEM ETF: 59.90[4] - GF GEM ETF: 60.01[4] - ChinaAMC Hang Seng Tech ETF: 54.81[4] - ChinaAMC Hang Seng ETF: 63.75[4] - ChinaAMC HK-Hang Seng ETF: 63.63[4] - Huaan Mitsubishi UFJ Nikkei 225 ETF: 63.21[4] - ChinaAMC Nomura Nikkei 225 ETF: 62.65[4] - GF Nasdaq 100 ETF: 59.68[4] - Guotai Nasdaq 100 ETF: 60.09[4] - Bosera S&P 500 ETF: 63.67[4] - Penghua Dow Jones Industrial Average ETF: 58.87[4] - Huatai-PB Southern East Asia Saudi Arabia ETF: 44.60[4] - Huaan Germany (DAX) ETF: 51.84[4] - Huaan France CAC40 ETF: 56.31[4]