- The AI-based global asset allocation model suggests a weight of 74.76% for the government bond index, 24.97% for SHFE gold, and 0.27% for the Hang Seng Index for February[5][44] - The model's performance in January showed a monthly return of -0.25%, compared to the benchmark strategy's return of 0.14%[5][44] - Historical performance from January 2021 to January 2026 indicates an annualized return of 7.22%, a Sharpe ratio of 1.07, and a maximum drawdown of 6.66%[46] - The stock-bond allocation model, based on macro timing and risk budgeting, suggests stock weights of 10.19%, 16.91%, and 70.00% for conservative, balanced, and aggressive profiles, respectively, for February[6][50] - The model's performance in January showed monthly returns of 3.65%, 1.22%, and 0.39% for aggressive, balanced, and conservative profiles, respectively[6][50] - Historical performance from January 2005 to January 2026 indicates annualized returns of 20.15%, 10.85%, and 5.87% for aggressive, balanced, and conservative profiles, respectively[51][57] - The dividend timing model recommends a 100% position in the CSI Dividend Index for February[7][58] - The model's performance shows an annualized return of 15.85%, an annualized volatility of 17.26%, a maximum drawdown of -21.22%, and a Sharpe ratio of 0.90[7][59] - The model's recent one-month return is 0.00%, compared to the CSI Dividend Total Return Index's return of 3.76%[7][59]

Group 1: Macro Insights - The report highlights that the recent volatility in gold and silver prices is primarily driven by market momentum reversals, with silver attracting high leverage and speculative funds since November 2025 [2][5] - The report anticipates that after the appointment of the new Federal Reserve Chairman, there will be more interest rate cuts than the market expects, with short-term U.S. Treasury yields likely to decline [2][4] - The report notes that the recent decline in the manufacturing PMI does not indicate a weakening economy, as it reflects a temporary fluctuation rather than a downward trend [10] Group 2: Commodity Market Analysis - The report indicates that the recent crash in silver prices has led to liquidity risks that may spread to other commodities, particularly in the non-ferrous metals sector [5][6] - It emphasizes the importance of monitoring the support levels for gold prices, particularly the 60-day moving average, which is currently at $4,400 per ounce [5] - The report suggests that the Shanghai Futures Exchange has implemented measures to manage the risk of a one-sided market in silver futures [5] Group 3: Equity Market Outlook - The report predicts a rebound in the A-share market following the Spring Festival, driven by positive sentiment from performance forecasts and new developments in sectors like AI applications and commercial aerospace [6][10] - It advises a balanced ETF allocation in domestic equities, reflecting a cautious yet optimistic outlook for the market [11] Group 4: Bond Market Perspective - The report notes that the bond market is expected to see increased buying activity due to risk aversion and expectations of monetary easing, with 10-year yields projected to decline to around 1.80% [7][10] - It highlights that the recent adjustments in risk appetite have created trading opportunities in government bonds as a hedge against stock market volatility [4][7]

- 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]

- 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]