Quantitative Models and Construction Methods 1. Model Name: "Clock + Turning Point Improvement Method" Asset Rotation Model - **Model Construction Idea**: This model integrates macroeconomic risk factors with asset rotation strategies, leveraging the "investment clock" concept and improving turning point identification through a combination of momentum and phase judgment methods [8][23][24] - **Model Construction Process**: 1. Macro risk factors (e.g., economic growth, inflation, interest rates, credit, exchange rates, and term spreads) are used to determine the macroeconomic state [8] 2. The "investment clock" framework is applied to link macroeconomic states with asset performance. For example, recovery and overheating phases favor equities and commodities, while stagflation and recession phases favor bonds and gold [9][15] 3. Turning points in macroeconomic factors are identified using a combination of momentum and phase judgment methods: - Momentum is calculated as: $$ Momentum_t = X_t - \frac{1}{3}(X_{t-1} + X_{t-2} + X_{t-3}) $$ where \( X_t \) represents the macro factor value at time \( t \) [16] - Phase judgment uses a 38-month sine wave to identify the current phase of macro factors, categorizing them into upward, downward, top, or bottom regions [21][22] 4. Asset scores are calculated based on the macro factor states, and risk allocation is adjusted accordingly. Initial risk weights are set as large-cap stocks: small-cap stocks: bonds: commodities: gold = 1:1:1:0.5:0.5. Positive scores double the risk allocation, while negative scores halve it [24] 5. Backtesting is conducted over the period from January 2011 to December 2023 [25] - **Model Evaluation**: The model demonstrates strong performance in terms of returns, risk control, and drawdown management, achieving nearly 10% annualized returns while maintaining low volatility and drawdowns [27] --- Model Backtesting Results 1. "Clock + Turning Point Improvement Method" Asset Rotation Model - **Total Return**: 242.45% - **Annualized Return**: 9.93% - **Annualized Volatility**: 6.83% - **Sharpe Ratio**: 1.45 - **Maximum Drawdown**: 6.31% - **Win Rate**: 73.08% [27] 2. Benchmark Equal-Weighted Portfolio - **Total Return**: 83.59% - **Annualized Return**: 4.78% - **Annualized Volatility**: 10.99% - **Sharpe Ratio**: 0.43 - **Maximum Drawdown**: 20.63% - **Win Rate**: 55.77% [27] --- Quantitative Factors and Construction Methods 1. Factor Name: Macro Risk Factors - **Factor Construction Idea**: These factors aim to capture various dimensions of macroeconomic risks, including economic growth, inflation, interest rates, credit, exchange rates, and term spreads, providing a comprehensive view of the macroeconomic environment [8] - **Factor Construction Process**: 1. **Economic Growth**: - Indicators: Industrial production YoY, PMI, retail sales YoY - Processing: HP filtering and volatility-weighted averaging - Interpretation: Positive values indicate economic expansion [8] 2. **Inflation**: - Indicators: PPI YoY, CPI YoY - Processing: HP filtering and volatility-weighted averaging - Interpretation: Positive values indicate rising inflation [8] 3. **Interest Rates**: - Indicators: Bond indices (1-3 years), money market indices - Processing: Equal-weighted portfolio construction and net value calculation - Interpretation: Negative values indicate falling interest rates and loose monetary conditions [8] 4. **Exchange Rates**: - Indicators: Gold prices (Shanghai and London) - Processing: Equal-weighted long-short portfolio construction - Interpretation: Positive values indicate currency depreciation [8] 5. **Credit**: - Indicators: Corporate bond indices (AAA) vs. government bond indices - Processing: Duration-neutral portfolio construction - Interpretation: Positive values indicate widening credit spreads and tighter credit conditions [8] 6. **Term Spreads**: - Indicators: Short-term vs. long-term bond indices - Processing: Duration-neutral portfolio construction - Interpretation: Positive values indicate widening term spreads [8] --- Factor Backtesting Results 1. Macro Risk Factors (July 2025 State) - **Economic Growth**: Upward (Recovery phase) - **Inflation**: Downward - **Interest Rates**: Downward - **Credit**: Downward - **Exchange Rates**: Downward - **Term Spreads**: Downward [36]

Group 1 - COMEX gold prices experienced a rise and subsequent decline, while SGE gold showed a slight correction, indicating market volatility [1] - The performance of gold-related ETFs varied, with Huaxia ETF (518850) rising nearly 25% year-to-date and reaching a record high of 4.92 billion yuan in product scale as of July 1 [1] - The gold stock ETF (159562) increased by 1.1%, with a year-to-date gain of approximately 42%, significantly outperforming the gold price increase [1] Group 2 - London spot gold prices saw a cumulative increase of 25.7% in the first half of 2025, marking the largest half-year gain since the second half of 2007 [1] - Experts suggest that factors such as geopolitical conflicts, a weakening dollar, and central bank gold purchases continue to support gold prices, with expectations of a continued upward trend in the second half of the year [1] - Recent U.S. economic data showed better-than-expected results, contributing to a rebound in precious metals after a period of decline, while the dollar index remains on a downward trend [2]

Quantitative Models and Construction Methods Model Name: Macro Risk Factor-Based Asset Rotation Model - **Model Construction Idea**: The model utilizes macroeconomic risk factors to guide asset allocation decisions, aiming to optimize returns while controlling risks[5][8]. - **Model Construction Process**: 1. **Macro Risk Factor System**: Six macro risk factors are constructed using economic growth, inflation, interest rates, exchange rates, credit, and term spread indicators[8]. 2. **Investment Clock**: The model incorporates the "growth-inflation clock" and "interest rate-credit clock" to understand asset performance under different macroeconomic conditions[9][10][11]. 3. **Phase Judgment Method**: The model uses factor momentum and phase judgment methods to identify macroeconomic turning points[16][17][21][22]. 4. **Asset Rotation Model**: Combining the investment clock and phase judgment methods, the model adjusts asset allocation based on current macroeconomic conditions[23][24]. 5. **Backtesting Period**: The model is backtested from January 2011 to December 2023[25]. 6. **Performance Metrics**: The model's performance is evaluated using total return, annualized return, annualized volatility, Sharpe ratio, maximum drawdown, and win rate[27]. - **Model Evaluation**: The model demonstrates excellent performance in terms of returns, risk control, and drawdown management, achieving nearly 10% annualized returns with controlled risk exposure[27]. Model Backtesting Results - **Macro Risk Factor-Based Asset Rotation Model**: - Total Return: 242.45%[27] - Annualized Return: 9.93%[27] - Annualized Volatility: 6.83%[27] - Sharpe Ratio: 1.45[27] - Maximum Drawdown: 6.31%[27] - Win Rate: 73.08%[27] Quantitative Factors and Construction Methods Factor Name: Macro Risk Factors - **Factor Construction Idea**: The factors are designed to capture various aspects of the macroeconomic environment, providing a comprehensive risk perspective[8]. - **Factor Construction Process**: 1. **Economic Growth**: Constructed using industrial added value, PMI, and retail sales growth, processed with HP filtering and weighted by volatility inverse[8]. 2. **Inflation**: Constructed using PPI and CPI growth, processed with HP filtering and weighted by volatility inverse[8]. 3. **Interest Rates**: Constructed using bond indices and money market fund indices, weighted equally[8]. 4. **Exchange Rates**: Constructed using gold prices in Shanghai and London, forming an equal-weighted long-short portfolio[8]. 5. **Credit**: Constructed using corporate bond and government bond indices, forming a duration-neutral portfolio[8]. 6. **Term Spread**: Constructed using short-term and long-term bond indices, forming a duration-neutral portfolio[8]. - **Factor Evaluation**: The factors provide a detailed and comprehensive view of macroeconomic risks, aiding in better asset allocation decisions[8]. Factor Backtesting Results - **Economic Growth Factor**: Upward trend[36] - **Inflation Factor**: Downward trend[36] - **Interest Rate Factor**: Tight interest rate, loose credit[36] - **Credit Factor**: Downward trend[36] - **Exchange Rate Factor**: Downward trend[36] - **Term Spread Factor**: Downward trend[36] Monthly Performance Review (May 2025) - **Model Performance**: - Monthly Return: -0.29%[30] - Benchmark Return: 0.3%[30] - Excess Return: -0.6%[30] - **Asset Allocation**: - Large Cap Stocks: 5.3%[34] - Small Cap Stocks: 3.01%[34] - Bonds: 69.95%[34] - Commodities (excluding gold): 12.84%[34] - Gold: 8.9%[34] Next Month's Allocation Suggestion (June 2025) - **Model Allocation**: - Large Cap Stocks: 1.91%[35] - Small Cap Stocks: 0.96%[35] - Bonds: 88.54%[35] - Commodities (excluding gold): 2.79%[35] - Gold: 5.81%[35] - **Risk Allocation**: - Large Cap Stocks: 0.06[35] - Small Cap Stocks: 0.06[35] - Bonds: 4[35] - Commodities (excluding gold): 0.125[35] - Gold: 1[35]

Group 1 - The core viewpoint is that gold prices are experiencing fluctuations influenced by recent market movements and global economic factors, with significant inflows into gold ETFs indicating strong investor interest [1][2] - On May 16, the Shanghai Gold Exchange saw a strong opening for gold, with related ETFs also rising, reflecting a positive market sentiment [1] - The World Gold Council reported that global physical gold ETFs saw inflows of approximately $11 billion in April, with the Asia-Pacific region leading the way with a record inflow of about $7.3 billion [1] Group 2 - Northeast Securities noted that the current gold price trend shows similarities to last year, suggesting a period of adjustment is necessary for the market to stabilize [2] - The combination of stagflation risks and slowly declining interest rates is expected to support gold prices in the medium term, while global asset rebalancing and a weakening dollar may attract long-term capital into the gold market [2]

消息面上，最新数据显示，美国4月PPI环比意外下跌0.5%，其中服务价格下降0.7%，创2009年以 来最大单月跌幅。鲍威尔发表言论，美联储正在调整其总体政策制定框架，零利率已不再是一个基本情 况，需要重新考虑就业不足和平均通胀率的措辞，并预计4月PCE降至2.2%，通胀预期减弱，将会继续 提升降息前景，而会支持金价。隔夜COMEX黄金期货涨1.74%报3243.90美元/盎司。 今日开盘，金价强势反弹，SGE黄金9999涨幅达1.7%，相关ETF——黄金基金ETF（518800）涨超 1.6%。 黄金基金ETF（518800）投资金交所现货合约，紧密跟踪金价走势，场内T+0交易，相较于购买黄 金实物资产等更加快捷方便，流动性也更好。 注：市场观点仅供参考，不构成任何投资建议或承诺。黄金基金ETF主要投资对象为黄金现货合 约，预期风险收益水平与黄金资产相似，不同于股票基金、混合基金、债券基金和货币市场基金。如需 购买相关基金产品，请您详阅基金法律文件，关注投资者适当性管理相关规定，提前做好风险测评，并 根据您自身的风险承受能力购买与之相匹配的风险等级的基金产品。基金有风险，投资需谨慎。 每日经济新闻 （责任编 ...