Quantitative Models and Construction Methods - **Model Name**: Convolutional Neural Network (CNN) for Price-Volume Data **Model Construction Idea**: The model leverages convolutional neural networks to analyze standardized graphical representations of price-volume data, aiming to predict future price trends. The learned features are then mapped to specific industry theme indices[76][78] **Model Construction Process**: 1. Standardize price-volume data into graphical formats for each stock within a specific time window[76] 2. Train a convolutional neural network to extract features from these graphical representations[76] 3. Map the learned features to industry theme indices, such as dividend low-volatility, banking, and real estate indices[76][78] **Model Evaluation**: The model effectively identifies industry themes based on price-volume patterns, providing actionable insights for sector allocation[76][78] Model Backtesting Results - **CNN Model**: Latest theme configurations include the following indices: 1. CSI Dividend Low Volatility Index (h30269.CSI) 2. CSI Banking Index (399986.SZ) 3. CSI 800 Banking Index (h30022.CSI) 4. CSI Mainland Real Estate Theme Index (000948.CSI) 5. CSI 800 Real Estate Index (399965.SZ)[78] Quantitative Factors and Construction Methods - **Factor Name**: Macroeconomic Indicators **Factor Construction Idea**: Macroeconomic factors are used to assess their impact on asset returns by identifying trends and significant events in historical data[51][52] **Factor Construction Process**: 1. Track 25 domestic and international macroeconomic indicators, such as PMI, CPI, PPI, and M2 growth rates[52] 2. Define four types of macroeconomic events: short-term peaks/troughs, continuous up/down trends, historical highs/lows, and trend reversals[52] 3. Use historical moving averages to classify macroeconomic trends (e.g., 3-month, 12-month averages) and analyze their impact on asset returns over the next month[54] **Factor Evaluation**: The approach identifies effective macroeconomic events that significantly influence asset returns, providing a robust framework for market trend analysis[52][54] Factor Backtesting Results - **Macroeconomic Factors**: 1. PMI (3-month moving average): Positive outlook for equities[55] 2. Social Financing Stock YoY Growth (1-month moving average): Neutral outlook[55] 3. 10-Year Treasury Yield (12-month moving average): Neutral outlook[55] 4. Dollar Index (1-month moving average): Neutral outlook[55]

Market Performance - The Sci-Tech 50 Index decreased by 4.03% over the last five trading days, while the ChiNext Index increased by 1.26%. The large-cap value index fell by 1.44%, and the large-cap growth index dropped by 0.48%. The Shanghai 50 Index declined by 2.47%, and the small-cap index represented by the CSI 2000 fell by 5.45%. The communication and banking sectors performed well, while basic chemicals and non-ferrous metals lagged behind [1]. Valuation Levels - As of March 20, 2026, the static PE of the CSI All Share Index is at 2.63%, with a two-standard deviation boundary at 4.62%. The CSI All Share Index's TTM PE is at the 82nd percentile, while the Shanghai 50 and CSI 300 are at 70% and 73%, respectively. The ChiNext Index is close to 63%, and the CSI 500 and CSI 1000 are both at 65%. The ChiNext Index's valuation style is relatively at the historical median level [2]. Thematic Investment Strategy - The latest thematic investment strategy focuses on low volatility dividends, banking, and real estate sectors. Specific indices include the CSI Low Volatility Dividend Index, CSI Banking Index, CSI 800 Banking Index, CSI Mainland Real Estate Theme Index, and CSI 800 Real Estate Index [2][3]. AI and Machine Learning Application - A convolutional neural network (CNN) is utilized to model price and volume data, mapping learned features to industry thematic sectors. This approach is based on research reports regarding AI recognition and classification of stock price trends [9]. Market Sentiment - The proportion of stocks above the 200-day long-term moving average is tracked, indicating market sentiment and potential trends [10]. ETF Scale Changes - The report includes observations on the changes in the scale of mainstream ETFs, reflecting shifts in investor preferences and market dynamics [11]. Risk Preference Tracking - The report monitors the risk preferences between equity and bond assets, providing insights into investor behavior and market conditions [12].

Group 1 - The core viewpoint of the news is that the real estate sector is showing strong performance, driven by policy initiatives such as Shanghai's acquisition of second-hand housing for rental projects, indicating a potential turning point for the industry [2][3]. - The CSI 800 Real Estate Index has increased by 3.34%, with leading stocks like China Merchants Shekou rising by 5.03%, New City Holdings by 5.0%, and Binjiang Group by 4.96% [2]. - The real estate ETF (159707), which tracks the CSI 800 Real Estate Index, has seen a price increase of 3.3% with a trading volume of 45.2278 million yuan, reflecting strong market interest [2]. Group 2 - Financial analysts believe that after years of bottoming out, the real estate sector is approaching a fundamental turning point, with expectations for effective policy measures to support recovery [3]. - The current price-to-book (PB) ratio of the CSI 800 Real Estate Index is 0.68, which is lower than 88% of the time over the past decade, indicating significant room for valuation recovery [3]. - The real estate ETF (159707) is noted for its concentration in top-tier companies, with over 90% of its weight in the top ten constituents, suggesting a strong focus on leading state-owned enterprises and quality developers [5].

Group 1 - The real estate sector showed resilience, with the CSI 800 Real Estate Index rising nearly 1% to reach a new high for the year, driven by significant gains in stocks like China Merchants Shekou (+3.86%) and Binjiang Group (+2.29%) [1] - The only ETF tracking the CSI 800 Real Estate Index (159707) saw a peak increase of 3% during trading, closing up 1.15% with a trading volume of nearly 80 million yuan and a substantial net subscription of 23.5 million units in a single day, indicating strong investor interest [1] Group 2 - The new round of housing market regulation in Shanghai has shown significant short-term effects, with new home transaction volumes increasing by over 30% in the first week and a total increase of 19% in the first month compared to the previous month, reflecting the policy's immediate impact on the market [3] - Analysts from Zhongyin Securities suggest that structural policy relaxations in major cities like Beijing, Shanghai, and Shenzhen may lead to a short-term rebound in the housing market, with a focus on companies with strong liquidity and product capabilities [3] - Guotou Securities anticipates improved new home sales due to increased supply from developers and the release of pent-up demand from relaxed regulations, alongside expectations of interest rate cuts [3] Group 3 - The current valuation of leading real estate companies, particularly state-owned enterprises, remains low, with the CSI 800 Real Estate Index's latest price-to-book (PB) ratio at only 0.8, indicating significant potential for valuation recovery [4] - Analysts from Guojin Securities recommend investing in real estate stocks due to the low valuations and the anticipated liquidity boost from potential interest rate cuts by the Federal Reserve [4] Group 4 - The real estate ETF (159707) focuses on top-tier real estate companies, with over 90% of its weight in the top ten constituents, highlighting a concentration in leading firms within the industry [6][7] - The current market environment favors leading real estate companies, which are expected to exhibit greater resilience amid industry challenges [7]

Group 1 - The real estate sector is showing multiple positive signals, suggesting continued attention to investment opportunities in this area [3] - The China Securities Index 800 Real Estate Index saw a rise, with major companies like China Merchants Shekou and Greenland Holdings increasing by over 2% [1][3] - The real estate ETF (159707) tracking the China Securities Index 800 Real Estate Index has experienced a seven-day consecutive increase, with a daily trading volume exceeding 410 million yuan and a net subscription of 10.5 million units [1][4] Group 2 - From January to August, national real estate development investment reached 60,309 billion yuan, a year-on-year decrease of 12.9%, with residential investment down by 11.9% [3] - New commodity housing sales area was 57,304 million square meters, down 4.7% year-on-year, while sales revenue was 55,015 billion yuan, a decrease of 7.3% [3] - The National Bureau of Statistics indicated that while the real estate market has experienced fluctuations, the year-on-year decline in sales and housing prices is narrowing, showing signs of stabilization [3] Group 3 - Major cities are implementing new real estate policies, with Shenzhen recently announcing measures to optimize housing policies, following similar actions in Beijing and Shanghai [3][4] - September is typically a period of intensive policy announcements in the real estate sector, with expectations for new supportive policies to be introduced [4] - The market is entering the traditional peak sales season of "Golden September and Silver October," which may lead to increased activity in the real estate market [4] Group 4 - The current price-to-book (PB) ratio of the China Securities Index 800 Real Estate Index is 0.77, indicating a significant undervaluation compared to historical levels [4] - Leading real estate companies, particularly state-owned enterprises, are expected to show resilience in sales and profitability due to their strong land reserves in core cities [6] - The real estate ETF (159707) is highlighted for its concentration on top-tier companies, with over 90% of its weight in the top ten constituents, making it a favorable investment option [6]

Group 1 - The core viewpoint of the news is that the China Securities 800 Real Estate Index has shown a slight decline on a specific trading day, while it has experienced an overall increase over the past month and three months [1] - The China Securities 800 Real Estate Index has increased by 3.40% in the last month, 7.47% in the last three months, and 0.35% year-to-date [1] - The top ten weighted companies in the China Securities 800 Real Estate Index include China Merchants Shekou (13.86%), Poly Developments (13.36%), and Vanke A (13.3%) [1] Group 2 - The market segments of the China Securities 800 Real Estate Index show that the Shanghai Stock Exchange accounts for 67.59% and the Shenzhen Stock Exchange accounts for 32.41% [2] - The sample of the China Securities 800 Real Estate Index is entirely composed of the real estate industry, with a 100.00% weight in this sector [3] - The index samples are adjusted biannually, with adjustments occurring on the next trading day after the second Friday of June and December [3]

Core Viewpoint - The real estate sector is showing strong performance, with the CSI 800 Real Estate Index rising by 2.41% as of July 25, indicating a positive market sentiment and potential recovery in the industry [1]. Group 1: Market Performance - The CSI 800 Real Estate Index increased by 2.41%, reflecting a robust performance in the real estate sector [1]. - Notable stocks include Zhangjiang Hi-Tech, which hit the daily limit, Hainan Airport rising by 4.35%, and New Town Holdings increasing by 3.28% [1]. - The only ETF tracking the CSI 800 Real Estate Index, the Real Estate ETF (159707), saw its market price rise by 2.19%, with a trading volume of 79.3055 million yuan [1]. Group 2: Investment Insights - Guolian Minsheng Securities highlights that the real estate sector's valuation remains at historical lows, with ongoing policy support aimed at stabilizing the market [2]. - There are signs of recovery in the core city land market expected by mid-2025, with resilient demand for improved housing creating valuation recovery opportunities for leading real estate companies [2]. - It is recommended to focus on leading central and state-owned enterprises and high-quality real estate companies that have strong land acquisition capabilities and good product quality in core urban areas [2][3]. Group 3: ETF Characteristics - The Real Estate ETF (159707) tracks the CSI 800 Real Estate Index, which includes 13 leading real estate companies, demonstrating a significant concentration of top-tier firms [3]. - The top ten constituent stocks account for over 90% of the ETF's weight, indicating a high concentration of central and state-owned enterprises [3]. - In the context of industry consolidation, leading real estate companies may exhibit greater resilience and potential for growth [3].