Group 1 - The core viewpoint of the article emphasizes that the influx of incremental funds has become a dominant variable in the short-term A-share market [1] - The market showed a rebound last week, with the CSI 300 index rising by 1.95%, the Shanghai Composite Index by 1.91%, and the CSI 500 index by 3.98% [3] - The sudden shift in the Middle East situation from conflict to peace has led to a significant impact on market dynamics, with a notable influx of funds supporting the A-share market [3][4] Group 2 - The domestic industrial profit data released last week indicated a continued decline, which aligns with expectations, reflecting the objective state of the Chinese economy [3] - The unexpected ceasefire in the Middle East led to a rapid revaluation of global risk assets, causing a sharp drop in oil prices and a rebound in both Chinese and U.S. stock markets [3][4] - The technical indicators showed multiple models triggering buy signals, indicating a strong upward momentum in the market [4] Group 3 - The main board is recommended to maintain a high position, following the model signals that turned bullish after last Tuesday's close [5] - The small and medium-sized stocks are also suggested to adopt a high position, benefiting from liquidity support and showing greater elasticity in the current market environment [5] - The overall market sentiment is characterized by a "dual bull" trend in both stocks and bonds, driven by the active participation of incremental funds [4]

Group 1 - The current bond market is undergoing significant changes, with risk-free yields continuing to decline and traditional bond investment returns sharply compressed. Many private bond products have seen yields drop below 1.8% in the first five months of this year, contrasting with an average return of 7.91% for the entire previous year. The era of "lying win" is over [1] Group 2 - In response to the reality of significantly reduced yield space, private institutions are upgrading their bond investment strategies. Many are shifting focus towards cross-border composite products to capture cross-market spreads or increase trading frequency to enhance returns. The traditional credit spread has compressed to historical lows, prompting institutions to increase allocations to dim sum bonds and domestic city investment bonds for base returns while controlling product drawdowns [3] Group 3 - The ability to trade effectively is crucial for enhancing returns in a low-interest-rate environment. Both private bond strategy products and public "fixed income +" products require strict drawdown control. The difficulty of active timing and asset switching has increased significantly, making precise timing and asset rotation essential. A disciplined investment strategy with clear risk budgeting and position control frameworks is necessary [4] Group 4 - To improve trading success rates, institutions need to enhance market monitoring and information collection. Keeping a close watch on bond price movements, fund flows, and new bond issuances has become a daily priority. The current bond market lacks trending opportunities and is highly uncertain, often affected by sudden events. Given the unattractive absolute yield levels, institutions must maintain competitive advantages through refined operations and strategic innovations within limited yield spaces [4]

- The report includes a global asset allocation model based on artificial intelligence, which uses machine learning to score and rank various assets for monthly equal-weighted allocation strategy[30][31] - The global asset allocation model suggests weights for May: government bond index (66.09%), Nasdaq index (17.59%), German DAX index (13.83%), and Nikkei 225 (2.49%)[30] - Historical performance of the global asset allocation model from January 2021 to April 2025 shows an annualized return of 13.76%, Sharpe ratio of 0.75, maximum drawdown of 16.53%, and excess annualized return of 9.02%[30][36] - The dynamic macro event factor-based stock-bond rotation strategy includes three different risk preference models: conservative, balanced, and aggressive[37] - The stock-bond allocation models for April show stock weights of 45% for aggressive, 13.82% for balanced, and 0% for conservative[37][39] - Historical performance of the stock-bond allocation models from January 2005 to April 2025 shows annualized returns of 19.93% for aggressive, 11.00% for balanced, and 6.06% for conservative[37][44] - The dividend timing model uses economic growth and monetary liquidity indicators to construct a timing strategy for the dividend index, showing an annualized return of 15.84%, maximum drawdown of -21.70%, and Sharpe ratio of 0.89[45][49] - The dividend timing model's recommended position for April is 0%, with most economic growth indicators showing bearish signals and cautious monetary liquidity signals[45] Model Performance Metrics - Global asset allocation model: annualized return 13.76%, Sharpe ratio 0.75, maximum drawdown 16.53%[30][36] - Stock-bond allocation models: annualized returns 19.93% (aggressive), 11.00% (balanced), 6.06% (conservative)[37][44] - Dividend timing model: annualized return 15.84%, Sharpe ratio 0.89, maximum drawdown -21.70%[45][49]

Core Viewpoint - The macroeconomic environment is experiencing significant fluctuations due to tariff impacts, with asset prices showing a "rebound" effect after initial adjustments, leading to increased volatility in global markets [1][2][3]. Group 1: Asset Performance - As of April 30, 2025, the performance ranking of major assets is as follows: Gold > Euro Stoxx > Nikkei > Chinese Bonds > Nasdaq > 0 > Sci-Tech 50 > CSI 300 > Dow Jones > Hang Seng > US Dollar > Hang Seng Tech > LME Copper > Crude Oil [1][13]. - Gold has shown a year-to-date increase of 26.5% and a monthly rise of 6%, leading in both returns and Sharpe ratio among major assets, although it faced a pullback in late April [1][17]. - The domestic stock market exhibited a "dumbbell" characteristic, with small-cap and stable dividend stocks outperforming large-cap stocks, as evidenced by a 5.0% increase in the micro-cap index [1][41]. Group 2: Macroeconomic Indicators - The April manufacturing PMI, services PMI, and construction PMI in China fell to 49.0%, 50.1%, and 51.9%, respectively, indicating initial impacts from external demand [3]. - The US economy is showing signs of negative impacts from trade tensions, with Q1 GDP growth adjusted for inflation recording a negative annualized rate, and consumer spending growth slowing to 1.8% [3]. - The Eurozone and Japan's manufacturing PMIs showed slight increases, indicating some resilience in their economies [3]. Group 3: Market Dynamics - The domestic bond market displayed a dual pricing characteristic of nominal growth and liquidity, with interest rates declining in early April due to tariff impacts and expectations of policy easing later in the month [2][4]. - The stock market is increasingly focused on "finding certainty," with a shift towards dividend-paying and stable sectors amid rising external demand concerns [2][4]. - The correlation between stocks and bonds has deepened, with the rolling 12-month correlation increasing from -0.26 to -0.30, indicating a stronger inverse relationship [28]. Group 4: Sector Performance - In April, only 4 out of 31 sectors recorded positive returns, with beauty care, agriculture, retail, and utilities leading the gains, while sectors like power equipment and telecommunications lagged due to tariff impacts [41][51]. - The real estate market showed a mixed performance, with new home sales declining while second-hand home sales maintained a high growth rate, reflecting resilience in major cities [53]. Group 5: Investment Strategies - The dividend asset timing model indicates a continued rise in dividend scores, suggesting a shift towards dividend-paying stocks as a strategy to mitigate uncertainty [6][7]. - The valuation macro deviation framework suggests that if nominal GDP growth can recover, there will be further room for reasonable valuation expansion in the market [8].

- The global asset allocation model uses machine learning to score and rank assets based on factor investment principles, constructing a monthly quantitative equal-weight strategy for global asset allocation[39][43][44] - The model's historical performance from January 2021 to March 2025 shows an annualized return of 6.45%, Sharpe ratio of 1.01, maximum drawdown of 6.66%, and excess annualized return of 1.28%, outperforming the benchmark across all dimensions[39][44][45] - The dynamic macro event factor-based stock-bond rotation strategy includes three risk preference models (conservative, balanced, aggressive), with April stock weights of 0%, 13.73%, and 25%, respectively[45][46][47] - The macro timing module and risk budget framework signal strengths for April are 50% for monetary liquidity and 0% for economic growth[45][46][48] - Historical performance of the stock-bond rotation strategy from January 2005 to March 2025 shows annualized returns of 20.02% (aggressive), 11.02% (balanced), and 6.03% (conservative), all outperforming the benchmark[45][51][47] - The dividend timing model recommends a 100% allocation to the CSI Dividend Index for April, with economic growth indicators mostly bearish and monetary liquidity signals positive[53][54][52] - The dividend timing strategy achieves an annualized return of 16.86%, maximum drawdown of -21.22%, and Sharpe ratio of 0.95, significantly improving stability compared to the CSI Dividend Total Return Index[53][54][52]