期货盯盘神器案例分享 相关链接 玻璃、纯碱、棕榈油、红枣的期限结构隐含了什么不为人知的秘密？ ...

MFM 张周 教授 固定收益课程从债券基础知识框架入手，逐步深入带领学生们了解到全球债券市场概况，构成市场参与者的类型以及债券是如何在全球发行、流通以及分类 的，从而对债券投资有了直观的认识。带领学生们进阶掌握了固定收益与衍生品的结合，对其定价方式与实际应用有了初步了解，并对收益率曲线变动进行 免疫的高级交易策略包括使用利率期货、期权、互换和互换期权展开学习。 加拿大阿尔伯塔大学客座教授、加拿大里贾纳大学希尔商学院金融学正教授(终身教职)。加拿大曼尼托巴大学金融学博士、特许金融分析师（CFA）。曾获 Leaders Council Scholar，Viterra Faculty Fellow及CMA Faculty Fellow等荣誉称号。主要研究领域为企业资本结构及融资方式, 企业内部控制及公司治理。 主讲教授 MFM 李倩 教授 管理学博士，西安交通大学经济与金融学院教授、博士生导师，美国加州大学伯克利分校哈斯商学院访问学者，主要从事行为金融学、投资组合管理、风险 管理等方面的教学与研究工作。近年来在《当代经济科学》、《证券市场导报》、《系统工程》、《管理学报》、Organizational Dynami ...

盈利预期期限结构因子历史表现良好，走势稳定性高。 将盈利预期期限结构"动量 ff"因子与传统分析师预期 调升因子合成后，得到的"合成动量 ff"因子走势进一步改 善，兼具高收益与稳定性。 ► 选股组合表现 在沪深 300、中证 500、中证 800、中证 1000 内分别选择 "合成动量 ff"因子值排名前 50、50、100、100 名的股票， 构成选股组合，组合历史表现良好。 证券研究报告|金融工程研究报告 [Table_Date] 2025 年 7 月 2 日 [Table_Title] 6 月份超额收益加速，上半年全部组合大幅跑赢基准——盈利预 期期限结构选股月报 202507 [Table_Summary] ► 盈利预期期限结构因子 分析师在某一时点会对上市公司未来多年的盈利做出预 测，我们将预期盈利随未来年度变化的趋势称为盈利预期期 限结构。 2025 年 6 月，沪深 300 选股组合、中证 500 选股组合、 中证 800 选股组合、中证 1000 选股组合超额收益加速，大幅 跑赢基准，超额收益分别为 4.29%、2.36%、3.72%、1.69%。 2025 年前 6 个月，沪深 300、中 ...

以下文章来源于巴顿比格斯 ，作者巴顿比格斯 多晶硅方面，日前发改委开会约谈光伏硅企挺价，叠加成本端焦煤价格大幅反弹，当然更重 要的原因是过去两年价格大幅下行，全行业几乎没有企业盈利，叠加多晶硅盘面贴水过大， 市场悲观过度，这就是索罗斯说的价格反身性的问题，价格就是最大的基本面。 巴顿比格斯 . 历史不会重复，但是它自然成韵。 文 | 巴顿比格斯 来源 | 巴顿比格斯 编辑 | 杨兰 审核 | 浦电路交易员 今日焦煤继续大涨，沪铜大涨，广期所品种表现更为抢眼，多晶硅接近涨停，工业硅大涨 4%，碳酸锂上涨3%，最熊的品种居然大涨，这是为何？ 广期所三傻出道即巅峰，大哥工业硅一上市就玩起自由落体，从20000点起步硬是给投资者 表演了波地心引力加强版，最低跌到7000点；二哥多晶硅更绝，从最高45000开始，活像个 高开低走型网红，没撑过三集就跌破成本线。最绝是三弟碳酸锂，带着新能源贵族光环登 场，结果从24万跌到6万，持仓者含泪改编歌词：是谁在耳边说，跌跌不休~ 现在，广期所三傻真的要翻身了吗？ 消息总是走在盘面后面。今天对工业硅影响最大的是硅企主产区减产：新疆硅企突发减产， 工业硅下周产量预期下调。根据市场反馈 ...

期货盯盘神器案例分享 相关链接 甲醇、PTA、棉花、白糖的期限结构隐含了什么不为人知的秘密？ ...

Group 1 - Haier Consumer Finance successfully issued a financial bond of 1 billion yuan with a 3-year term and an interest rate of 2.2% [1] - The lead underwriter for the bond issuance was CITIC Securities, with several other banks participating in the underwriting process [1] - In 2024, Haier Consumer Finance issued three tranches of ABS totaling 4.65 billion yuan and one financial bond of 1.5 billion yuan, indicating a significant increase in financing activities [1] Group 2 - The company increased its registered capital from 1.5 billion yuan to 2.09 billion yuan, a growth rate of nearly 40% [1] - By the end of 2024, the company's on-balance-sheet asset size reached 29.3 billion yuan, showing a notable increase compared to the previous two years [1] - Other consumer finance companies have also been issuing financial bonds and ABS this year, with a total issuance of 10.6 billion yuan across multiple institutions [2]

张一格是中国人民银行金融研究所金融学硕士，曾任兴业银行资金营运中心投资经理，国泰基金基金经 理，融通基金固收投资总监、基金经理；2023年9月，他加入摩根资产管理中国，现任债券投资总监。 "客户投资喜欢'看后视镜'，我们要做的，是让每一次回望都更安心。"摩根资产管理中国债券投资总监 张一格在接受证券时报记者采访时如此阐述其投资哲学。 在低利率的债市新常态下，这位拥有超19年金融从业经验的固收老将，带领团队在固收投资的"方寸之 地"精耕细作，以严苛的回撤控制与精细化的策略布局，为投资者打造"防御型底仓"的优选工具。 预判重于事后补救 当前时点，张一格指出杠杆策略性价比凸显。"央行3月中旬以来持续呵护资金面，资金利率下行，信用 债与利率债相对资金利差走阔。"他表示，若宽松流动性环境延续，适度加杠杆有望成为收益增强的重 要来源。 面对近年来信用债市场偶发的风险事件，张一格与其团队在2024年5月推出了摩根瑞欣利率债基金，该 基金定位鲜明——只投国债与政策性金融债等利率债品种，彻底规避信用风险，目标客群是完全回避信 用风险的投资人，包括商业银行等机构及散户。 摩根瑞欣利率债基金成立一年多以来，业绩表现稳步前进。截至2 ...

期货盯盘神器案例分享 什么是期限结构？期限结构隐含了什么不为人知的秘密？ 相关链接 ...

国债期货市场周报 华金期货 研究院 2025/6/4 一、国债期货宏观及市场展望 • 周度宏观及消息面 • 国债后市展望 上周国债期货震荡。资金方面，上周央行净投放6566亿元。上周十年期国债利率略降；长期看，十年 期国债利率处于历史低位。 技术上，T2509合约短期价格位于40日均线附近。操作方面，国债市场价格高位震荡，利率仍处低位 区间，中长期看上方空间有限，短期逢低买入。 国内消息：中国5月财新制造业PMI录得48.3，较4月下降2.1个百分点，2024年10月来首次跌至临界点 以下。 国外消息：美国财政部公布了其最新国债回购操作的结果，其规模却达到了前所未有的程度：高达100亿 美元，这是美国财政部有史以来规模最大的单次国债回购操作。 二、国债期货行情 • 价格走势：上周国债期货区间震荡 数据来源：博易大师、华金期货 三、国债收益率变化 • 收益率变化：上周长期利率下降，收益率利差收窄 | 日期 | 3M | 1Y | 2Y | 5Y | 10Y | | --- | --- | --- | --- | --- | --- | | 2025-05-23 | 1.4138 | 1.4461 | 1.471 ...

Quantitative Models and Construction Methods 1. Model Name: Commodity Term Structure Simulation Portfolio - **Model Construction Idea**: This is a long-short strategy that dynamically holds long positions in commodities with high roll yields and short positions in commodities with low roll yields. The strategy aims to capture the term structure premium in commodity markets while reducing dependency on single market trends[33][35][34]. - **Model Construction Process**: 1. **Roll Yield Factor**: The roll yield is calculated to measure the contango or backwardation state of a commodity. 2. **Dynamic Positioning**: Commodities with high roll yields are dynamically allocated long positions, while those with low roll yields are allocated short positions. 3. **Portfolio Balancing**: The portfolio is rebalanced periodically to maintain the desired exposure to the roll yield factor[35][38]. - **Model Evaluation**: The strategy demonstrates flexibility in adapting to market risks and provides stable returns even in weak market trends[34]. 2. Model Name: Commodity Time-Series Momentum Simulation Portfolio - **Model Construction Idea**: This strategy captures medium- to long-term trends in commodity prices using multiple technical indicators. It dynamically allocates long positions to upward-trending assets and short positions to downward-trending assets[33][35]. - **Model Construction Process**: 1. **Trend Indicators**: Technical indicators such as moving averages and momentum are used to identify price trends. 2. **Dynamic Positioning**: Commodities with upward trends are allocated long positions, while those with downward trends are allocated short positions. 3. **Portfolio Rebalancing**: Positions are adjusted periodically based on updated trend signals[35][45]. - **Model Evaluation**: The strategy effectively tracks price trends but may underperform in volatile or trendless markets[45]. 3. Model Name: Commodity Cross-Sectional Inventory Simulation Portfolio - **Model Construction Idea**: This strategy uses inventory data to capture fundamental changes in commodity markets. Commodities with declining inventories are allocated long positions, while those with increasing inventories are allocated short positions[33][35]. - **Model Construction Process**: 1. **Inventory Factor**: Changes in inventory levels are calculated to assess supply-demand dynamics. 2. **Dynamic Positioning**: Commodities with declining inventories are dynamically allocated long positions, while those with increasing inventories are allocated short positions. 3. **Portfolio Rebalancing**: Positions are adjusted periodically based on updated inventory data[35][49]. - **Model Evaluation**: The strategy is effective in capturing fundamental supply-demand imbalances but may be sensitive to data accuracy and reporting delays[49]. --- Model Backtesting Results 1. Commodity Term Structure Simulation Portfolio - **Annualized Return**: 3.03% (YTD 2025)[33][38] - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 2. Commodity Time-Series Momentum Simulation Portfolio - **Annualized Return**: -1.33% (YTD 2025)[45] - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 3. Commodity Cross-Sectional Inventory Simulation Portfolio - **Annualized Return**: 2.88% (YTD 2025)[49] - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned --- Quantitative Factors and Construction Methods 1. Factor Name: Roll Yield Factor - **Factor Construction Idea**: Measures the contango or backwardation state of a commodity to capture the term structure premium[35]. - **Factor Construction Process**: 1. Calculate the roll yield as the difference between the spot price and the futures price. 2. Normalize the roll yield across commodities to ensure comparability. 3. Rank commodities based on their roll yields and allocate positions accordingly[35]. 2. Factor Name: Trend Factor - **Factor Construction Idea**: Captures medium- to long-term price trends using technical indicators[35]. - **Factor Construction Process**: 1. Use moving averages, momentum, and other technical indicators to identify trends. 2. Normalize trend signals across commodities to ensure comparability. 3. Rank commodities based on their trend strength and allocate positions accordingly[35]. 3. Factor Name: Inventory Factor - **Factor Construction Idea**: Measures changes in inventory levels to capture supply-demand imbalances[35]. - **Factor Construction Process**: 1. Calculate the percentage change in inventory levels over a specified period. 2. Normalize inventory changes across commodities to ensure comparability. 3. Rank commodities based on their inventory changes and allocate positions accordingly[35]. --- Factor Backtesting Results 1. Roll Yield Factor - **Annualized Return**: Not explicitly mentioned - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 2. Trend Factor - **Annualized Return**: Not explicitly mentioned - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 3. Inventory Factor - **Annualized Return**: Not explicitly mentioned - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned