Economies.com的分析师今日最新观点：现货 黄金价格在近期日内交易中延续涨势，持续刷新历史新 高，并已触及我们此前分析中预期的5200美元阻力位目标。这一强劲表现受到价格持续运行于50日指数 移动平均线（EMA50）上方的支撑，进一步巩固了短期内主导看涨趋势的稳定性。另一方面，相对强 弱指标（RSI）持续为看涨路径提供利多信号。尽管指标目前处于超买区，可能引发价格波动或暂时性 的获利了结，但这并不会动摇主导上升趋势的强度。因此，我们预计黄金在接下来的日内交易中将继续 上行，若能有效突破5200美元阻力位，后市目标将看向下一阻力位5400美元。 ...

1. 情绪模型观点：市场情绪平稳，价量一致性高 位震荡 根据《从结构化视角全新打造市场情绪择时模型》文中提到的构建思路，目前我们用于构建市场情绪结构指标用到的细分指标如下表。 | 指标简称 | 含义 | 情绪指示方向 | | --- | --- | --- | | 行业间交易波动率 | 资金在各板块间的交易活跃度 | 正向 | | 行业交易拥挤度 | 极值状态判断市场是否过热 | 负向 | | 价量一致性 | 资金情绪稳定性 | 正向 | | 科创 50 成交占比 | 资金风险偏好 | 正向 | | 行业涨跌趋势性 | 刻画市场轮涨补涨程度，趋势衡量 | 正向 | | BSI | 价格体现买方和卖方力量相对强弱 | 正向 | | 主力买入力量 | 主力资金净流入水平 | 正向 | | PCR 结合 VIX | 从期权指标看市场多空情绪 | 正向或负向 | | 融资余额占比 | 资金对当前和未来观点多空 | 正向 | 在指标合成方法上，模型采用打分的方式， 根据每个分项指标所提示的情绪方向和所处布林轨道位置计算各指标分数，指标分数可分为（-1，0，1）三种情况，最终对各个指标分数等权求和。最终的情绪结构指标为求 ...

Economies.com的分析师今日最新观点： 布伦特原油价格在收复部分失地后，盘中小幅震荡，并成功摆 脱了相对强弱指标上明显的超卖状态，触及50日均线阻力位，但由于短期内看跌修正波的主导地位，其 涨幅有所回落，这威胁到盘中上行的稳定性，使其容易受到潜在信号的影响。 ...

Group 1 - The core viewpoint of the article highlights that silver prices are experiencing a bullish trend, driven by a combination of macroeconomic factors and industrial demand, with significant inflows into the silver market [1][1][1] - The largest silver ETF, iShares Silver Trust (SLV), saw an increase in holdings by 533.01 tons, marking the largest single-day increase since January 2023, bringing total holdings to 16,599.25 tons [1][1][1] - Industrial demand for silver has risen to 55%, driven by sectors such as photovoltaics and electric vehicles, while global visible inventories remain below safe levels, supporting the price recovery of silver [1][1][1] Group 2 - A survey conducted by Kitco News among 352 retail investors indicated that over 50% of respondents expect silver to be the best-performing metal again by 2026 [1][1][1] - In the latest trading session, silver prices surged, indicating a short-term bullish trend, supported by positive signals and trading above the 50-day EMA, which suggests potential for further gains [1][1][1]

Group 1: Gold Market - Gold prices are attempting to close above $4240 [1] - The market is reacting to rising US Treasury yields, leading to profit-taking after a strong rebound [4] - The relative strength index remains at a moderate level, indicating potential for additional upward momentum in the short term [4] Group 2: Silver Market - The gold-silver ratio has risen above 79.00, causing silver prices to retreat to the $53.00 level [1][7] - Technically, silver needs to stay above the resistance level of $52.60-$52.80 to gain additional upward momentum in the short term [7] Group 3: Platinum Market - Platinum attempted to break through the resistance level of $1620-$1630 but lost momentum and retreated [9] - Platinum remains within the range between support at $1520-$1530 and resistance at $1620-$1630 [9]

Core Viewpoint - International spot silver is experiencing downward pressure and is poised to break the key support level of $47.80, as indicated by recent analyst insights [1][2]. Technical Analysis - The current price of international spot silver is consistently trading below the 50-day exponential moving average, creating negative pressure [1][2]. - A steep bearish correction wave is dominating the trend line, contributing to effective downward pressure on silver prices [1][2]. - The Relative Strength Index (RSI) has moved out of the oversold territory and is now showing negative overlapping signals, which further intensifies the downward pressure on international spot silver [1][2].

Core Viewpoint - International spot silver is experiencing downward pressure and is poised to break the critical support level of $47.80 [1] Price Movement - Recent trading shows a decline in international spot silver prices, indicating a buildup of momentum to breach the $47.80 support level [1] - The price is consistently trading below the 50-day exponential moving average, creating negative pressure [1] Technical Indicators - The relative strength index has moved out of the oversold territory, but current signals indicate negative overlap, which intensifies the downward pressure [1]

Quantitative Models and Construction Methods 1. Model Name: Industry Relative Strength (RSI) Model - **Model Construction Idea**: This model identifies leading industries by calculating their relative strength (RS) based on historical price performance over different time windows [10] - **Model Construction Process**: 1. Use 29 first-level industry indices as the configuration targets [10] 2. Calculate the price change rates for the past 20, 40, and 60 trading days for each industry index [10] 3. Rank the industries based on their price change rates for each time window and normalize the rankings to obtain RS_20, RS_40, and RS_60 [10] 4. Calculate the average of the three rankings to derive the final RS value: $ RS = \frac{RS_{20} + RS_{40} + RS_{60}}{3} $ [10] 5. Industries with RS > 90% by the end of April are identified as potential leading industries for the year [10] - **Model Evaluation**: The model successfully identified key annual industry trends, such as high dividend, resource products, exports, and AI, which were validated by market performance throughout the year [10][12] 2. Model Name: Industry Sentiment-Trend-Crowding Framework - **Model Construction Idea**: This framework provides two industry rotation strategies based on market conditions: 1. High sentiment + strong trend, avoiding high crowding (aggressive strategy) 2. Strong trend + low crowding, avoiding low sentiment (conservative strategy) [6][14] - **Model Construction Process**: 1. Evaluate industries based on three dimensions: sentiment, trend, and crowding [6][14] 2. Use sentiment as the core metric for the aggressive strategy, with crowding as a risk control factor [14] 3. Use trend as the core metric for the conservative strategy, avoiding low-sentiment industries [14] 4. Allocate weights to industries based on their scores in the three dimensions [6][14] - **Model Evaluation**: The framework is effective in adapting to different market conditions and has shown strong performance in historical backtests [6][14] 3. Model Name: Left-Side Inventory Reversal Model - **Model Construction Idea**: This model identifies industries with potential for recovery by analyzing sectors in distress or those with low inventory pressure and high analyst optimism [24] - **Model Construction Process**: 1. Identify industries currently in distress or recovering from past distress [24] 2. Focus on sectors with low inventory pressure and potential for restocking [24] 3. Incorporate analyst long-term positive outlooks for these industries [24] - **Model Evaluation**: The model effectively captures recovery opportunities in industries undergoing inventory restocking cycles, providing significant absolute and relative returns [24] --- Model Backtesting Results 1. Industry Relative Strength (RSI) Model - **Annualized Return**: Not explicitly mentioned - **Excess Return**: Not explicitly mentioned - **Information Ratio (IR)**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Monthly Win Rate**: Not explicitly mentioned - **Performance Highlights**: - Industries with RS > 90% by April 2024 included coal, utilities, home appliances, banking, petrochemicals, communication, non-ferrous metals, agriculture, and automotive [10] - These industries showed strong performance, with key themes being high dividends, resource products, exports, and AI [10][12] 2. Industry Sentiment-Trend-Crowding Framework - **Annualized Return**: 22.1% (long-only portfolio) [14] - **Excess Return**: 13.8% (annualized) [14] - **Information Ratio (IR)**: 1.51 [14] - **Maximum Drawdown**: -8.0% [14] - **Monthly Win Rate**: 68% [14] - **Performance Highlights**: - 2023 excess return: 7.3% [14] - 2024 excess return: 5.7% [14] - 2025 YTD excess return: 2.8% [14] 3. Left-Side Inventory Reversal Model - **Annualized Return**: Not explicitly mentioned - **Excess Return**: - 2023: 17.0% (relative to equal-weighted industry benchmark) [24] - 2024: 15.4% (relative to equal-weighted industry benchmark) [24] - 2025 YTD: 7.8% (relative to equal-weighted industry benchmark) [24] - **Information Ratio (IR)**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Monthly Win Rate**: Not explicitly mentioned - **Performance Highlights**: - Absolute return: - 2023: 13.4% [24] - 2024: 26.5% [24] - 2025 YTD: 26.4% [24] --- Quantitative Factors and Construction Methods 1. Factor Name: Sentiment Factor - **Factor Construction Idea**: Measures the overall sentiment of an industry to identify high-growth opportunities [14] - **Factor Construction Process**: 1. Evaluate the sentiment of each industry based on relevant metrics (not explicitly detailed in the report) [14] 2. Rank industries by sentiment scores [14] - **Factor Evaluation**: Sentiment is a core metric in the aggressive strategy of the Industry Sentiment-Trend-Crowding Framework, providing strong signals for high-growth opportunities [14] 2. Factor Name: Trend Factor - **Factor Construction Idea**: Measures the strength of market trends to identify industries with strong momentum [14] - **Factor Construction Process**: 1. Evaluate the trend of each industry based on relevant metrics (not explicitly detailed in the report) [14] 2. Rank industries by trend scores [14] - **Factor Evaluation**: Trend is a core metric in the conservative strategy of the Industry Sentiment-Trend-Crowding Framework, offering a simple and replicable approach to industry allocation [14] 3. Factor Name: Crowding Factor - **Factor Construction Idea**: Measures the level of crowding in an industry to identify overbought or underbought sectors [14] - **Factor Construction Process**: 1. Evaluate the crowding level of each industry based on relevant metrics (not explicitly detailed in the report) [14] 2. Rank industries by crowding scores [14] - **Factor Evaluation**: Crowding is used as a risk control factor in both aggressive and conservative strategies of the Industry Sentiment-Trend-Crowding Framework [14] --- Factor Backtesting Results 1. Sentiment Factor - **Annualized Return**: Not explicitly mentioned - **Excess Return**: Not explicitly mentioned - **Information Ratio (IR)**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Monthly Win Rate**: Not explicitly mentioned 2. Trend Factor - **Annualized Return**: Not explicitly mentioned - **Excess Return**: Not explicitly mentioned - **Information Ratio (IR)**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Monthly Win Rate**: Not explicitly mentioned 3. Crowding Factor - **Annualized Return**: Not explicitly mentioned - **Excess Return**: Not explicitly mentioned - **Information Ratio (IR)**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Monthly Win Rate**: Not explicitly mentioned

Core Viewpoint - The euro is experiencing a decline against the US dollar, currently trading around 1.16, influenced by political developments in France and the potential widening of the yield spread between French and German government bonds [1] Group 1: Currency Movement - As of August 27, the euro to US dollar exchange rate is at 1.1626, reflecting a decrease of 0.14% from the previous closing rate of 1.1643 [1] - Analysts suggest that the euro may drop to around 1.14 if the yield spread between French and German 10-year government bonds increases from 78 basis points to 90 basis points due to potential temporary elections in France [1] Group 2: Political Influence - French Prime Minister Borne is seeking parliamentary support for a significant budget-cutting plan, which could impact the euro's performance [1] - The political dynamics in France are expected to be a key driver for the euro's movement, especially if market conditions remain unaffected by unexpected US data or comments from Trump regarding tariffs [1] Group 3: Technical Analysis - The euro is currently testing the support level of the 20-day simple moving average at 1.1608, with bearish sentiment emerging as the relative strength index (RSI) has fallen below the neutral line [1] - Short positions are targeting a drop to 1.1550, indicating a prevailing bearish outlook in the near term [1]