Market Overview - The Asia-Pacific stock markets experienced a significant decline, with the Nikkei 225 index falling by 3.48% and the South Korean KOSPI dropping by 6.49%, triggering a trading halt [1] - In the A-share market, all three major indices fell over 3%, with the Shanghai Composite Index barely holding above the 3800-point mark [1][3] - The total trading volume in the Shanghai and Shenzhen markets reached 2.43 trillion yuan, an increase of 144.7 billion yuan compared to the previous trading day, with over 5100 stocks declining [3] Sector Performance - The power sector showed notable activity, with several stocks hitting the daily limit up, driven by rising international oil prices due to escalating geopolitical tensions in the Middle East [6] - Conversely, sectors such as precious metals, agriculture, food, and aviation faced significant declines, with stocks like Chifeng Jilong Gold and Sichuan Gold hitting the daily limit down [6] Geopolitical Impact - Analysts suggest that the core pressure on the market stems from evolving geopolitical conflicts, particularly the ongoing tensions between the U.S. and Iran, which have led to a bearish sentiment in the A-share market [7] - The volatility in the market is exacerbated by high-frequency trading, resulting in increased fluctuations in individual stocks [7] Future Outlook - Some brokerage firms remain optimistic about the future performance of the A-share market, suggesting that the current adjustment is a result of technical, funding, and emotional factors, with strong support around the 3800-point level [7] - Analysts recommend focusing on low-volatility assets in the short term, with an emphasis on sectors like coal, agriculture, insurance, and technology, while also considering cyclical sectors if geopolitical tensions ease [8]

Group 1 - The core viewpoint of the article highlights that the Kexin AI ETF Boshi (588790.SH) experienced a decline of 3.92% on February 2, 2026, despite a significant net inflow of 287 million yuan from major funds (transactions over 1 million yuan) [1] - The fund's latest trading volume reached 934 million shares, with a total transaction amount exceeding 830 million yuan, ranking first among comparable funds [1] - The Kexin AI ETF Boshi has several off-market connection classes, including Class A (023520), Class C (023521), and Class E (023989) [1]

Quantitative Models and Construction Methods 1. Model Name: XinXuan ETF Absolute Return Strategy - **Model Construction Idea**: The strategy aims to achieve absolute returns and long-term relative returns against A-share equities by selecting and trading ETFs from the XinXuan ETF pool [11] - **Model Construction Process**: - The strategy uses the "drawer method" to test equity ETFs in the pool - Past three-year performance: annualized return of 14.23%, maximum drawdown of 8.6%, Sharpe ratio of 1.44 (in-sample) - 2024 YTD performance: total return of 34.07%, excess return of 19.64% over equal-weighted ETFs, Sharpe ratio of 1.18, maximum drawdown of 6.3%, volatility of 17.11%, Calmar ratio of 3.67 [11] - **Evaluation**: Demonstrates strong performance with low drawdowns and high Sharpe ratio [11] 2. Model Name: All-Weather Multi-Asset Multi-Strategy ETF Risk Parity Strategy - **Model Construction Idea**: Combines sector rotation, style rotation, and risk parity to enhance returns while reducing portfolio volatility [14][16] - **Model Construction Process**: - Asset allocation includes: - Commodities: Gold ETFs - US equities: S&P 500 ETFs - Domestic equities: sector/style/size rotation - Domestic bonds: 10-year and 30-year government bond ETFs [16] - Risk parity is applied to distribute assets effectively across different strategies and asset classes [16] - **Evaluation**: Improves precision in ETF usage and achieves effective diversification [16] 3. Model Name: China-US Core Asset Portfolio - **Model Construction Idea**: Combines trend-following RSRS strategy and technical reversal strategies for four strong-trend assets: Baijiu, dividends, gold, and Nasdaq [20] - **Model Construction Process**: - Annualized return since 2015: 33.77%, excess return of 13.16% over equal-weighted indices, Sharpe ratio of 1.64, maximum drawdown of 18.23%, volatility of 17.8% [20] - **Evaluation**: Outperforms equal-weighted indices with strong returns and moderate risk [20] 4. Model Name: High Growth/Dividend Rotation Strategy - **Model Construction Idea**: Rotates between high-growth and dividend strategies based on signals [23] - **Model Construction Process**: - High-growth signal: Allocates 50% to ChiNext ETF and 50% to STAR 50 ETF - Dividend signal: Allocates to Dividend Low Volatility ETF (pre-Feb 2024) and 50% to Dividend Low Volatility ETF + 50% to Central SOE Dividend 50 ETF (post-Feb 2024) - Annualized return since 2021: 19.44%, excess return of 21.51% over equal-weighted indices, Sharpe ratio of 0.88, maximum drawdown of 22.91%, volatility of 24.08% [23] - **Evaluation**: Strong returns but higher volatility and drawdowns [23] 5. Model Name: Dual Bond LOF Enhanced Strategy - **Model Construction Idea**: Enhances bond-heavy portfolios by adjusting weights based on volatility normalization [26] - **Model Construction Process**: - Divides assets into Dual Bond LOF and other products (aligned with China-US Core Asset Portfolio) - Calculates weekly returns and volatility for each group - Normalizes the inverse of volatility to determine weights, ensuring higher allocation to bonds due to lower volatility [26] - Annualized return since 2019: 6.73%, Sharpe ratio of 2.55, maximum drawdown of 2.42%, volatility of 2.55% [26] - **Evaluation**: Effectively reduces risk while maintaining competitive returns [26] 6. Model Name: Structured Risk Parity Strategy (QDII) - **Model Construction Idea**: Incorporates QDII products into a risk parity framework, focusing on domestic long-term bonds, QDII equities, gold, and domestic dividend ETFs [29] - **Model Construction Process**: - Asset allocation includes: - Commodities: Gold ETFs - QDII: Nasdaq, Nikkei, German, S&P, and other international ETFs - Domestic dividends: Bank ETFs, Dividend Low Volatility ETFs - Domestic bonds: 5-year, 10-year, and 30-year government bond ETFs - 2024 YTD performance: total return of 24.84%, maximum drawdown of 2.38%, volatility of 4.83%, Sharpe ratio of 2.87 [29] - **Evaluation**: Strong performance with low drawdowns and high Sharpe ratio [29] --- Model Backtest Results 1. XinXuan ETF Absolute Return Strategy - Total return: 34.07% - Annualized return: 23.08% - Maximum drawdown: -6.30% - Volatility: 17.11% - Sharpe ratio: 1.18 [32] 2. High Growth/Dividend Rotation Strategy - Total return: 53.14% - Annualized return: 35.23% - Maximum drawdown: -22.04% - Volatility: 33.88% - Sharpe ratio: 0.99 [32] 3. China-US Core Asset Portfolio - Total return: 61.21% - Annualized return: 40.24% - Maximum drawdown: -10.86% - Volatility: 16.79% - Sharpe ratio: 1.98 [32] 4. Dual Bond LOF Enhanced Strategy - Total return: 9.26% - Annualized return: 6.47% - Maximum drawdown: -2.26% - Volatility: 3.32% - Sharpe ratio: 1.30 [32] 5. Structured Risk Parity Strategy (QDII) - Total return: 24.84% - Annualized return: 17.01% - Maximum drawdown: -2.38% - Volatility: 4.83% - Sharpe ratio: 2.87 [32] 6. All-Weather Multi-Asset Multi-Strategy ETF Risk Parity Strategy - Total return: 19.84% - Annualized return: 13.67% - Maximum drawdown: -3.62% - Volatility: 4.39% - Sharpe ratio: 2.49 [32]

Investment Rating - The report suggests a focus on industries with low PB-ROE ratios, particularly financials, computing, defense, pharmaceuticals, and electrical equipment, indicating a potential for undervalued reversals [4][5]. Core Insights - Since April 2025, global trade tariff conflicts have led to significant volatility in capital markets, with markets in Japan, Germany, and the US rising by 5-10% compared to pre-tariff levels, while Chinese asset prices have slightly declined [3][4]. - The report emphasizes the importance of performance benchmarks for public funds, highlighting that financials, dividends, and computing are major underweight sectors [3][4]. - The report identifies a calendar effect where certain sectors like electronics and military are expected to yield higher absolute returns in June and July [3][4]. Summary by Sections Industry Rotation Review and Outlook - Consumer, pharmaceutical, banking, and dividend assets have shown superior performance [12]. Fund Analysis - New regulations for public funds stress the significance of performance benchmarks, with financials, dividends, and computing being the main underweight sectors [3][4]. Market Trading Characteristics - Assets that have seen declines for four consecutive years, such as pharmaceuticals and certain consumer goods, are beginning to stabilize, while real estate and liquor sectors have yet to show improvement [3][4]. Economic Conditions, Valuation, and Capital Chips - The current PB-ROE framework favors industries poised for undervalued reversals, including financials, computing, defense, pharmaceuticals, and electrical equipment [4][5]. Industry Policies - The report discusses ongoing policies aimed at stabilizing capital markets, boosting consumption, and addressing internal competition, with a focus on new productivity [4][5]. 2025 Industry Allocation - The report provides a detailed allocation table for the second half of 2025, indicating sectors with potential for absolute returns [12].