燃料油日报 | 2025-08-22 盘面跟随原油小幅反弹，短期不确定性仍存 市场分析 上期所燃料油期货主力合约日盘收涨1.15%，报2732元/吨；INE低硫燃料油期货主力合约日盘收涨1.19%，报3483 元/吨。 在经历连续下跌后，原油价格出现企稳反弹迹象，并带动FU、LU盘面小幅上涨。短期需要关注俄美乌之间会谈的 进展，美国对俄罗斯制裁的态度变化将影响市场情绪，带来额外价格波动。如果没有超预期的宏观与地缘事件， 中期油市下行压力仍存。 就燃料油自身基本面而言，高硫油基本面与市场结构依然偏弱，短期压力有限。但未来随着夏季结束，中东当地 需求回落，叠加欧佩克增产趋势，中东燃料油发货可能还有增长空间，高硫燃料油市场面临进一步转松的预期。 但如果裂解价差调整充分，吸引炼厂端需求显著改善，市场结构有望企稳并再度走强。 低硫燃料油方面，当前市场压力有限，但整体并无短缺预期。国产量持续处于低位，但海外供应已有所回升，外 盘近期呈现边际转弱态势。中期视角下，由于低硫燃料油剩余产能较为充裕，一旦裂解利润适宜将吸引供应释放， 且航运业碳中和趋势将导致低硫燃料油市场份额被逐步替代，市场上方阻力较大。 | 图1：新加坡高硫3 ...

Report Details - Report Date: July 27, 2025 [1] - Report Title: Nanhua Treasury Bond Futures Weekly Report Investment Rating - No investment rating information is provided in the report. Core Viewpoints - This week, the bond market experienced a significant adjustment. The main pressure came from risk assets, and the tightening of the capital market worsened the situation. Treasury bonds and commodities are two types of assets with highly similar but opposite price trends. When commodities rebounded, the bond market faced substantial pressure and significant pullbacks [2]. - In the medium - to long - term, fundamentals and liquidity expectations are the two most crucial factors for the bond market. The report does not believe that the fundamentals have changed drastically in just one week, nor does it think that production restrictions can solve demand - side problems. The significant fluctuations in commodities and the bond market are related to the long - term low (high) valuation and low - volatility market structure, and market behavior has amplified the intensity of the market [2]. Summary by Relevant Catalog 1. Market Data - **Futures Data**: The settlement prices of various Treasury bond futures contracts decreased this week. For example, the 10 - year Treasury bond futures T2509.CFE closed at 108.195, down 0.57%; the 30 - year Treasury bond futures TL2509.CFE closed at 118.120, down 2.00% [8]. - **Spread Data**: In terms of inter - period spreads, T2509 - T2512 was - 0.015, down 0.667; in terms of inter - variety spreads, 2TS - T was 301.109, up 0.183 [8]. - **Spot Bond Yields**: The yields of various Treasury bonds and policy - bank bonds increased this week. For example, the yield of the 10 - year Treasury bond rose 6.79 BP to 1.73%, and the yield of the 30 - year Treasury bond rose 8.70 BP to 1.98% [8]. - **Funding Rates**: Bank - to - bank pledged repurchase rates and SHIBOR rates showed different degrees of increase. For example, DR001 rose 6.08 BP to 1.52%, and SHIBOR1M rose 0.90 BP to 1.55% [8]. 2. Graphical Analysis - **Bond Yield Curve Changes**: The report shows the changes in Treasury bond yields at different time points, reflecting the trends in yield curve movements [10][12]. - **Bond Spread Trends**: The report presents the trends of inter - period spreads and inter - variety spreads, such as the 2TF - T and 2TS - T spreads [21]. - **Treasury Bond Term Spread Trends**: The report shows the trends of 5Y - 2Y BP, 10Y - 5Y BP, and 10Y - 2Y BP [25].

Report Summary 1) Report Industry Investment Rating - High - sulfur fuel oil: Oscillating [3] - Low - sulfur fuel oil: Oscillating [3] 2) Core Viewpoints - The crude oil price has been oscillating strongly since the OPEC meeting, and the unilateral prices of FU and LU are supported by the cost side. However, there is an expectation of a looser balance sheet in the medium - term crude oil market, which may limit the upside space of prices. The recent oil price decline has also led to a weaker market drive [1]. - The current market structure of high - sulfur fuel oil is weak, with spot discounts, monthly spreads, and crack spreads continuously declining. Although there are still structural support factors, the crack spreads need to further adjust to attract the return of refinery demand [1]. - The market structure of low - sulfur fuel oil has been stable recently, supported by the strong performance of overseas diesel. The overall supply pressure is limited due to the significant year - on - year decline in domestic production in the first half of the year. However, the surplus production capacity is abundant, and the long - term carbon - neutral trend in the shipping industry will suppress the market [1]. - The current market structure of low - sulfur fuel oil is slightly stronger than that of high - sulfur fuel oil, and the high - low sulfur spread has been widening recently, but the structural contradiction has not completely reversed, and there is no room for a significant increase in the spread [2]. 3) Strategy Summary - High - sulfur: Maintain an oscillating trend [3] - Low - sulfur: Maintain an oscillating trend [3] - Cross - variety: Short the FU crack spread (FU - Brent or FU - SC) on rallies [3] - Cross - period: Gradually take profit on the previous FU reverse spread positions [3] - Spot - futures: No strategy [3] - Options: No strategy [3]

Report Industry Investment Rating No information provided in the content. Core View of the Report The report is the first in a series of special reports on the SMC system, introducing the basic theory of single - cycle market structure. SMC is a new technical analysis and trading methodology. The core of the SMC system is market structure, which determines the price trend direction. The core logic of the SMC strategy is to enter the market relying on strong points and aim at weak points as targets. Four key conclusions are derived from relevant concepts, which are the important cornerstones for the subsequent development of the theory [2][3][10]. Summary According to the Directory 1. Introduction: SMC System Introduction - SMC (Smart Money Concepts) is a new, complete, and systematic technical analysis and trading methodology, originating from ICT. It became popular after 2020, especially in the foreign exchange and cryptocurrency trading communities [2][6]. - The basic idea of SMC is to follow the trading behavior of "smart money" to achieve high - probability or high - profit - loss ratio trading. However, the so - called "smart money" may not exist in reality, and its effectiveness is explained by the more fundamental ICT theory [2][6]. - The advantages of the SMC system include a complete theoretical system, "naked K analysis" without relying on technical indicators, relatively less subjective components and high degree of regularization, and a complete trading system with clear entry, exit, and target frameworks [2][7]. - The SMC system consists of five modules: market structure, institutional supply and demand, order flow, liquidity, and trading strategies. Market structure is the core, used to determine the price trend direction, and other parts revolve around it [8]. 2. Basic Concepts and Expectations of Market Structure - Market structure refers to a series of high and low points and the bands formed between them, which can be divided into upward and downward structures according to the arrangement of high and low points [11]. - Structure break (BOS) means any of the HH, HL, LH, LL in the market structure is broken. If the HL in an upward structure or the LH in a downward structure is broken, a trend reversal is expected, but this is only a probability - based expectation [14][17]. - The generation of high and low points: In an upward structure, HH is confirmed after a certain - amplitude callback, while HL is objectively determined after the HH is broken. The situation in a downward structure is similar [18][21]. - After a structure break, a callback at the same level as the structure is expected, which helps answer questions about chasing high after a new high is broken [21][22]. - Swing high, swing low, and swing range: Swing high and low are the latest high and low points at a certain moment, and the swing range is the area between them. They are mainly used to assist in judging structure breaks and introducing the concepts of strong and weak points [25]. - Strong points and weak points: When a structure break occurs, the unbroken swing point is the strong point, and the broken one is the weak point. Strong points are expected not to be broken, and weak points are expected to be broken. The core logic of the SMC strategy is to enter the market relying on strong points and aim at weak points [27][31]. 3. Premium and Discount - For the callback band after a structure break, the mid - point of the previous band price range is the fair value, the area above 50% is the premium area, and the area below 50% is the discount area. They are used to assist in judging the general areas for long and short positions and when the callback band ends [32]. 4. Summary - The report mainly introduces the basic theory of single - cycle market structure, with the core logic of the SMC strategy being to enter the market relying on strong points and aim at weak points. Four key conclusions are derived: trend reversal is expected when a turning point is broken; a callback at the same level as the structure is expected after a structure break; strong points are expected not to be broken, and weak points are expected to be broken; the probability of the end of the callback band increases as it approaches the strong point, especially when the callback amplitude reaches more than 50% [35][36][39].

Group 1 - The core viewpoint of the news highlights that Xiaomi Group reported record-high revenue and profit for Q1 2025, with total revenue reaching RMB 111.3 billion, a year-on-year increase of 47.4% [1] - In terms of business segments, the revenue from the mobile and AIoT division was RMB 92.7 billion, up 22.8% year-on-year, while the revenue from the smart electric vehicle and AI innovation division was RMB 18.6 billion [1] - The adjusted net profit for the quarter was RMB 10.7 billion, marking a historical high with a year-on-year growth of 64.5% [1] Group 2 - Citic Securities predicts that macroeconomic factors, AI developments, and market structure will drive a continued reversal in the Hong Kong stock market in the second half of the year [1] - The report notes that the revenue share of Hong Kong-listed companies from the Americas has dropped to 1.8% in 2024, with a higher weight in real estate and consumer sectors, making it more attractive compared to A-shares amid domestic economic recovery [1] - The performance of Hong Kong tech giants is expected to exceed profit expectations in the second half of the year, similar to the post-ChatGPT release performance in the US stock market [1] Group 3 - Notable investment targets include the Hang Seng ETF (159920), Hang Seng Technology Index ETF (513180), and Hang Seng Consumer ETF (513230), among others [2]

Quantitative Factors and Construction Methods 1. Factor Name: Market Style Factors - **Construction Idea**: The market style factors track the balance and volatility between different market styles, such as large-cap vs. small-cap and value vs. growth[11][13] - **Construction Process**: - **Style Balance**: Measure the relative performance of large-cap vs. small-cap stocks and value vs. growth stocks to determine the market's style preference[11] - **Style Volatility**: Calculate the fluctuations in the relative performance of these styles over time to assess the stability of the market's style preference[11] - **Evaluation**: The market style factors showed a balanced preference between large-cap and small-cap stocks, as well as between value and growth stocks. Additionally, the volatility of these styles continued to decline, indicating a more stable market environment[11][13] 2. Factor Name: Market Structure Factors - **Construction Idea**: These factors analyze the dispersion of returns, sector rotation, and trading concentration to understand the structural dynamics of the market[11][13] - **Construction Process**: - **Return Dispersion**: Measure the excess return dispersion across industry indices to evaluate the variability in sector performance[11] - **Sector Rotation**: Assess the speed of sector rotation by tracking changes in sector leadership over time[11] - **Trading Concentration**: Calculate the proportion of trading volume concentrated in the top 100 stocks and the top 5 industries to gauge market concentration[11] - **Evaluation**: The market structure factors indicated a decline in return dispersion, slower sector rotation, and reduced trading concentration, suggesting a more evenly distributed market environment[11][13] 3. Factor Name: Market Activity Factors - **Construction Idea**: These factors measure the overall activity and liquidity of the market through volatility and turnover rates[12][13] - **Construction Process**: - **Volatility**: Calculate the index-level volatility to assess market stability[12] - **Turnover Rate**: Measure the turnover rate of the market to evaluate trading activity[12] - **Evaluation**: The market activity factors showed a decline in both volatility and turnover rates, reflecting reduced market activity, likely influenced by the holiday period[12][13] 4. Factor Name: Commodity Market Factors - **Construction Idea**: These factors analyze the performance, momentum, and liquidity of various commodity sectors[27][30] - **Construction Process**: - **Trend Strength**: Measure the strength of price trends in different commodity sectors, such as energy, metals, and agriculture[27] - **Basis Momentum**: Calculate the basis momentum, particularly for the metals sector, to assess the relative strength of futures prices compared to spot prices[27][30] - **Volatility**: Track the volatility levels across commodity sectors to evaluate risk[27][30] - **Liquidity**: Measure the liquidity of commodity sectors to assess trading ease[27][30] - **Evaluation**: The commodity market factors showed mixed performance, with strong trends in energy and metals, weaker trends in agriculture, and high volatility across sectors. Liquidity remained stable overall[27][30] 5. Factor Name: Options Market Factors - **Construction Idea**: These factors analyze the implied volatility and skewness of options to infer market sentiment and expectations[35] - **Construction Process**: - **Implied Volatility**: Measure the implied volatility levels of options on major indices, such as the SSE 50 and CSI 1000, to gauge market uncertainty[35] - **Skewness**: Analyze the skewness of call and put options to understand market expectations for upward or downward movements[35] - **Evaluation**: The options market factors indicated a divergence in sentiment, with increased optimism for small-cap stocks (CSI 1000) and reduced optimism for large-cap stocks (SSE 50). This suggests a potential shift in market preference post-holiday[35] 6. Factor Name: Convertible Bond Market Factors - **Construction Idea**: These factors evaluate the valuation and trading activity of the convertible bond market[38] - **Construction Process**: - **Valuation**: Measure the average conversion premium of convertible bonds to assess their relative attractiveness[38] - **Trading Activity**: Track the trading volume and turnover in the convertible bond market to evaluate market interest[38] - **Evaluation**: The convertible bond market factors showed a slight increase in valuation, with trading activity continuing to recover, indicating improving market sentiment[38] --- Factor Backtesting Results 1. Market Style Factors - **Style Balance**: Balanced between large-cap and small-cap, as well as value and growth[11][13] - **Style Volatility**: Continued decline in volatility, indicating stability[11][13] 2. Market Structure Factors - **Return Dispersion**: Declined, indicating less variability in sector performance[11][13] - **Sector Rotation**: Slowed down, suggesting reduced changes in sector leadership[11][13] - **Trading Concentration**: Decreased, reflecting a more evenly distributed market[11][13] 3. Market Activity Factors - **Volatility**: Declined, indicating reduced market risk[12][13] - **Turnover Rate**: Decreased, reflecting lower trading activity[12][13] 4. Commodity Market Factors - **Trend Strength**: Strong in energy and metals, weak in agriculture[27][30] - **Basis Momentum**: Highest in metals, declined in other sectors[27][30] - **Volatility**: High across all sectors[27][30] - **Liquidity**: Stable overall[27][30] 5. Options Market Factors - **Implied Volatility**: Increased for both SSE 50 and CSI 1000, indicating higher uncertainty[35] - **Skewness**: Positive for CSI 1000 (small-cap optimism), negative for SSE 50 (large-cap caution)[35] 6. Convertible Bond Market Factors - **Valuation**: Slight increase in average conversion premium[38] - **Trading Activity**: Continued recovery in trading volume[38]

分析师：柏逸凡 登记编号：S0890524100001 分析师：程秉哲 登记编号：S0890522110001 投资要点 本报告统计时间为2025.04.21-2025.04.25。 上周，美国在中美关税问题态度上仍在反复，风险未进一步上升，但尚未显著改善。不过受中央汇金等稳股市力量支撑， A股大盘延续稳健走势，银行股表现较好，但其他行业板块多数以快速轮动为主，科技板块波动偏大，赚钱效应有限。 权益市场 ，市场风格方面，大小盘风格仍以大盘为主，价值成长风格偏向价值；风格波动方面，大小盘风格波动与价值 成长风格波动继续下降。市场结构方面，上周，行业指数超额收益离散度上升，成分股上涨比例基本持平，行业轮动速度 上升，交易集中度方面，前100个股成交额占比从低位回升，前5行业成交额占比继续下降，显示行业成交集中度下行。市 场活跃度方面，市场波动率从高位迅速回落，换手率有所降低，显示尽管关税问题仍待解决，但股市已经逐步回复平静。 商品市场方面 ，趋势强度表现分化，能化、黑色板块趋势性较强，有色、农产品板块趋势性较弱；基差动量方面，有色 板块最高，黑色板块快速下降；波动率方面，各板块波动率维持在高位；流动性方面，各板块 ...