好的谢谢徐老师的分享我是东正衍生品研究院宏观团队的分析师吴茂盈然后今天晚上我主要和大家分享的是商品市场的一些观点主要想讲的两个内容就是我们当前的商品市场是在这家什么样的一个 邏輯以及後期來講的話我們大概是怎麼樣去看這個商品的多工配置的 其实从我们最近的一些报告其实也可以看出我们在六月上旬的时候我们当时发布的月报我们当时提示到的是宏观的这种强政策预期其实是在一个缓慢退潮的过程当中 然后基本面无论是国内还是国外其实都不太能支撑到商品持续的反弹也就是说我们当时在的这样一个我们逐渐由前面的这样一个强现实强预期的这样一个周期逐渐转移到了强预期弱现实的一个 一个转折点的过程当中然后我们在半年报当中也有一个观点就是认为金融市场所交易的这样一个乐观的预期和中美经济的这样一个实体的一个经济增长来讲它其实是有一个错位镜像的一个现象那么我们也能够看到在最近一两周的时间里面那么这种错位的镜像也已经逐渐走到了另一端 那么我们其实可以看到自从美国大选特朗普他出现了这样一个意外事件之后那么市场上对特朗普他大选上任的这种可能性是得到了进一步的提升那么这个对于金融市场来讲的话他的这种 它的这种概率的提升的话它其实更多的是去交易到了这样一个通胀 ...

各位投资人 大家下午好本次霍普投资的分享是2024年的一季度二季度的产品时更新和思路策略的一个预测首先是分析师介绍 本次分享主要包含七个部分第一部分是思慕FORF的投研体系第二部分的话是思慕策略的FORF市场分析主要是2024年的上半年那么第三部分的话是我们自上而下的一个环境试验型的产品筛选体系和思维联动的产品评价体系那么第四部分的话呢是自上而上的一个细分的策略研究和策略评价与预测 第五部分的话是我们针对2024年的下半年的市场展望与配置建议第六部分的话是我们分享一个专题研究就是银行理财视角的量化中心策略的一个分析第七部分的话是我们能够提供的报告与相关服务首先我们进行第一部分的一个分析思慕FORF的投影体系 斯穆霍夫投原体系我们主要是分为两个条线那么第一个部分的话是霍夫配置主要是自下而上的一个霍夫研究首先我们会去通过三个部分来去确定我们的一个霍夫配置的方案首先我们会从这个策略研究出发 从编制策略指数、策略特征的提取、策略表现的分析、策略标签的入库以及筛选标准的确定去形成了我们一个全市场范围内进行筛选的基础池这个基础池的入池标准是动态的我们以季度为单位进行更新 那么第二部分的话呢是我们在构建了基础词之后我们通过 ...

各位亲近的投资者大家下午好我是东正颜生品研究院的首席化工分析师杨潇今天下午的话非常欢迎大家来参加我们的半年半年度的策略会议首先将由我这边跟大家分享一下绿简 相关品种的关于下半年的一些看法嗯因为这个设备的原因我们暂时就不把这个PPT给全屏化了嗯就用这种模式跟大家做一个分享应该也是能够看清的首先我们现在说一下这个PVC稍等一下电话卡住了 嗯PVC的话下半年我们给了个标题啊就抵逆前行我觉得还是比较比较贴切因为从上半年的情况来看的话PVC当前确实是一个压力比较确实是处于一个相对压力比较大的这么一个 一个状态嗯简单讲就是我们能够看到它是一个比较典型的产能共生的一个格局首先呢就是嗯库存的话非常的高对吧我们可以看到这张图啊不管是中间的社会库存还是说左边的这个企业库存啊都会比较夸张但就是说可能社会库存会更加突更加明显一些因为它是一直处于一个 历史的高位 历史最高位而且春节之后几乎没有直话 甚至还小幅的累了一点但你说企业库存的话从春节之后是有所具化的但是绝对值还是相对比较偏高一些所以整体上的话PVC整个产业链其实现在都处于一个库存相对偏高的这么一个状态那么除了库存之外第二个比较明显点就是它的生产利润 嗯比较低就最右边的图啊就从 ...

各位投资者朋友大家下午好欢迎参加2024年东正期货中期投资策略会有色专场今天很荣幸请到东正衍生品研究院院长助理曹杨老师有色首席分析师宋伟达老师和有色分析师陈奕山老师带来铜铝碳酸铳的半年度展望那么首先就让我们有请曹杨老师带来关于铜的分享有请曹杨老师 好的各位投资者朋友大家下午好今天我们在这里给大家进行一个中期有色这一块的策略会的这样一种分享首先也非常感谢大家来参加我们的这样一个策略会我今天主要给大家分享的内容就是我们站在目前这个节点对中期同价怎么样一个看法包括相应的我们也提出了一些针对的一些策略 首先的话就是说一下我们目前的整体的一个观点从单边的这个角度来说的话我们认为这一轮的这个上涨趋势并没有结束目前可能是一个中场休息的一个阶段那么我们对于四季度的这样一个铜的一个价格 包括明年上半年的这样一个价格的这样一个看法依然是比较积极的但是呢就是说从节奏短期的这种节奏上来看的话 我们觉得要注意一下就是三季度可能出现的一些潜在的一些回调的一个风险但是这个回调的这个幅度呢我们目前看的并不是特别大我们觉得可能就是75000上下的这样一个幅度啊这是一个相对的低点也就是今年下半年在三季度看了一个相对的低点但是我们觉得整个 整个1 ...

各位投资者下午好欢迎大家参加东正气货中期策略会的能源与碳中和以及产业咨询专场我是东正饮食品研究院能源分析师安子薇今天下午的议题的话主要是会跟各位分享关于原油TRT以及产业咨询三个主题的下半年的一个观点我这边的话就先开始今天第一个议题然后跟各位分享一下关于原油市场下半年的一个看法 首先我们简单的回顾一下就是整个今年以来的话油价走势其实可以看到就是上半年其实就是今年整个波动率相对比较低然后上半年其实主要是对于需求供应这端的一个计价那么整个价格的高点的话其实是伴随着市场对于地缘冲突的这种交易相对比较 剧烈的这个时期就在四月上旬左右的话出现这个价格的高点其实之后的话因为整体的就是市场的这种风险溢价的情绪在回落所以整个价格进入到了一个相对下行的这个趋势当中然后其实从六月之后的话这个价格有一波反弹那么我们觉得话其实这一波的反弹可能主要是对于就是三季度整个这个需求出现改善预期的这么一个计价 那从整个三半年供需基本面的一个预期来看的话,我们觉得可能目前来说对于价格相对的这种偏压力的来源的话,其实主要是来自于需求这一段,就是整体上其实在二季度之后已经暴露出来,就是今年整个这种需求增速相对比较缓慢的一个趋势的话,其实已经是 就是 ...

周度报告—金融工程 金工大类资产配置周报 [Table_Rank] 报告日期： 2024 年 07 月 07 日 [Table_Summary] ★市场回顾 宽基指数方面，本周涨跌幅排名前五的宽基指数及其涨跌幅分 别为纳斯达克综指(3.5%)，日经 225(3.4%)，胡志明股市指数 (3.0%)，标普 500(2.0%)，道琼斯工业平均(0.7%)；本周涨跌幅 排名后五的宽基指数及其涨跌幅分别为北证 50(-2.4%)，中证 2000(-2.0%)，小盘成长(-2.0%)，科创 50(-1.9%)，中证 1000(-1.7%)； 本月涨跌幅排名前五的宽基指数及其涨跌幅分别为纳斯达克 综指(3.5%)，日经 225(3.4%)，胡志明股市指数(3.0%)，标普 500(2.0%)，道琼斯工业平均(0.7%)；本月涨跌幅排名后五的宽 基指数及其涨跌幅分别为北证 50(-2.4%)，中证 2000(-2.0%)，小 盘成长(-2.0%)，科创 50(-1.9%)，中证 1000(-1.7%)。 行业指数方面，本周涨跌幅排名前五的行业指数及其涨跌幅分 别为有色金属(2.6%)，商贸零售(2.4%)，钢铁(1.9%) ...

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Quantitative Models and Construction Methods Intertemporal Arbitrage Strategy - Momentum Factor - **Factor Name**: Momentum Factor - **Construction Idea**: The factor is based on the return of intertemporal arbitrage portfolios over the past k trading days[33] - **Construction Process**: - For IH, a one-year momentum factor is used - For IF and IC, equal-weighted momentum factors are constructed for 10, 20, 30, 40, 60, 80, 120, and 250 trading days - Multi-period momentum strategies are built based on these factors - Rebalancing is done at the closing price, with a single-side transaction cost of 0.05%[33] - **Evaluation**: The factor effectively captures intertemporal arbitrage opportunities, with varying performance across different indices[33] Intertemporal Arbitrage Strategy - Annualized Basis Rate Factor - **Factor Name**: Annualized Basis Rate Factor - **Construction Idea**: The factor identifies arbitrage opportunities by comparing the annualized basis rates of different contracts[39] - **Construction Process**: - At 14:45 each day, the annualized basis rates of contracts (excluding dividends) are calculated - Long positions are taken on contracts with the lowest annualized basis rates, and short positions on those with the highest - Contracts with less than 10 days to expiration are excluded - Rebalancing is done at the closing price, with a single-side transaction cost of 0.05%[39] - **Evaluation**: The factor demonstrates strong performance in identifying profitable arbitrage opportunities, particularly for IC and IM contracts[39] --- Model Backtesting Results Momentum Factor - **IH**: Cumulative return 21.0%, annualized return 5.9%, annualized volatility 7.6%, Sharpe ratio 0.77, maximum drawdown -7.6%, Calmar ratio 0.77, monthly win rate 58%, profit-loss ratio 1.564[34] - **IF**: Cumulative return 8.8%, annualized return 2.6%, annualized volatility 5.5%, Sharpe ratio 0.46, maximum drawdown -7.0%, Calmar ratio 0.37, monthly win rate 49%, profit-loss ratio 1.560[34] - **IC**: Cumulative return 7.9%, annualized return 2.3%, annualized volatility 9.6%, Sharpe ratio 0.24, maximum drawdown -15.2%, Calmar ratio 0.15, monthly win rate 49%, profit-loss ratio 1.303[34] Annualized Basis Rate Factor - **IH**: Cumulative return 2.4%, annualized return 1.7%, annualized volatility 4.8%, Sharpe ratio 0.36, maximum drawdown -2.8%, Calmar ratio 0.61, monthly win rate 56%, profit-loss ratio 1.14[40] - **IF**: Cumulative return 10.9%, annualized return 7.8%, annualized volatility 5.7%, Sharpe ratio 1.37, maximum drawdown -2.9%, Calmar ratio 2.67, monthly win rate 67%, profit-loss ratio 1.61[40] - **IC**: Cumulative return 15.1%, annualized return 10.7%, annualized volatility 8.5%, Sharpe ratio 1.26, maximum drawdown -8.8%, Calmar ratio 1.22, monthly win rate 72%, profit-loss ratio 0.75[40] - **IM**: Cumulative return 11.8%, annualized return 8.4%, annualized volatility 8.7%, Sharpe ratio 0.97, maximum drawdown -7.9%, Calmar ratio 1.07, monthly win rate 56%, profit-loss ratio 1.06[40]

金工大类资产配置周报 [Table_Rank] 报告日期： 2024 年 06 月 30 日 [Table_Summary] ★市场回顾 宽基指数方面，本周涨跌幅排名前五的宽基指数及其涨跌幅分 别为日经 225(2.6%)，大盘价值(0.8%)，纳斯达克综指(0.2%)， 标普 500(-0.1%)，道琼斯工业平均(-0.1%)；本周涨跌幅排名后 五的宽基指数及其涨跌幅分别为科创 50(-6.1%)，小盘成长 (-4.2%)，中盘成长(-3.7%)，中证 1000(-3.2%)，中证 500(-3.1%)； 本月涨跌幅排名前五的宽基指数及其涨跌幅分别为纳斯达克 综指(6.0%)，标普 500(3.5%)，日经 225(2.8%)，道琼斯工业平均 (1.1%)，中证 REITs(收盘)(-0.5%)；本月涨跌幅排名后五的宽基 指数及其涨跌幅分别为中证 2000(-9.2%)，小盘成长(-8.7%)，中 证 1000(-8.6%)，北证 50(-8.1%)，小盘价值(-8.0%)。 行业指数方面，本周涨跌幅排名前五的行业指数及其涨跌幅分 别为银行(2.0%)，公用事业(1.0%)，石油石化(0.9%)，国防军工 ...

Quantitative Models and Construction Methods 1. Model Name: Market Neutral Strategy - **Model Construction Idea**: The market neutral strategy aims to achieve absolute returns by fully hedging market risks, primarily through quantitative methods[10][11][13] - **Model Construction Process**: - The strategy involves constructing a portfolio that is market-neutral, meaning it has no directional exposure to the market. - It uses quantitative models to select stocks based on alpha signals while hedging systematic risks through short positions in index futures or other instruments. - The strategy is often implemented with a focus on small- and mid-cap stocks, which are considered to have higher alpha potential[10][11][13] - **Model Evaluation**: The strategy is highly sensitive to market conditions, particularly during extreme market events. It demonstrates faster recovery compared to index-enhanced strategies due to its reliance on basis arbitrage advantages[13][14][57] 2. Model Name: Due Diligence Iteration Framework - **Model Construction Idea**: This framework is designed to enhance risk management and adaptability during extreme market conditions through pre-event monitoring, in-event response, and post-event optimization[53][55][56] - **Model Construction Process**: - **Pre-event Monitoring**: Utilizes composite risk control measures, fundamental analysis, and leading indicators such as the performance of top institutions and commodity market price discovery mechanisms[53][54] - **In-event Response**: Employs either passive intervention (accepting temporary drawdowns) or active intervention (manual adjustments to factor constraints and portfolio exposure)[55] - **Post-event Optimization**: Focuses on factor differentiation, self-developed risk control models, and T0 trading capabilities to mitigate future risks[56] - **Model Evaluation**: The framework highlights the importance of predictive and adaptive capabilities in managing extreme market scenarios, emphasizing the need for customized risk control models and real-time adjustments[53][55][56] --- Model Backtesting Results 1. Market Neutral Strategy - **Cumulative Return**: -3.28% (Full Market Index), -1.37% (Due Diligence Pool), -0.65% (50+ Neutral Advisory Index)[11][15] - **Annualized Return**: -17.64% (Full Market Index), -7.70% (Due Diligence Pool), -3.70% (50+ Neutral Advisory Index)[11][15] - **Sharpe Ratio**: -1.64 (Full Market Index), -1.29 (Due Diligence Pool), -0.71 (50+ Neutral Advisory Index)[11][15] - **Annualized Risk**: 12.60% (Full Market Index), 8.28% (Due Diligence Pool), 9.44% (50+ Neutral Advisory Index)[11][15] - **Maximum Drawdown**: 6.59% (Full Market Index), 4.02% (Due Diligence Pool), 3.82% (50+ Neutral Advisory Index)[11][15] 2. Due Diligence Iteration Framework - **Cumulative Return**: Not explicitly quantified but emphasizes recovery capabilities during extreme market conditions[53][55][56] - **Sharpe Ratio**: Not explicitly quantified but highlights the importance of predictive and adaptive measures to improve risk-adjusted returns[53][55][56] - **Maximum Drawdown**: Managed through pre-event monitoring and in-event adjustments, with specific examples of reduced drawdowns for certain managers[53][55][56] --- Quantitative Factors and Construction Methods 1. Factor Name: Composite Risk Control Measures - **Factor Construction Idea**: Enhance risk management by integrating multiple risk control indicators, including Barra factors, fundamental analysis, and market liquidity signals[53][54] - **Factor Construction Process**: - Use Barra factors to monitor tracking errors and style drift. - Incorporate fundamental analysis to identify nonlinear factor contributions. - Monitor top institutional performance and commodity market signals as leading indicators[53][54] - **Factor Evaluation**: The factor's predictive power is limited in normal market conditions but becomes critical during extreme events, emphasizing its role in early warning systems[53][54] 2. Factor Name: Nonlinear Alpha Factors - **Factor Construction Idea**: Focus on nonlinear contributions to alpha generation, leveraging fundamental research and advanced computational techniques[53][56] - **Factor Construction Process**: - Develop nonlinear factors based on fundamental data and machine learning models. - Integrate these factors into multi-factor models to enhance alpha generation[53][56] - **Factor Evaluation**: Nonlinear factors are increasingly important as traditional linear factors face diminishing returns, highlighting the need for innovation in factor construction[53][56] --- Factor Backtesting Results 1. Composite Risk Control Measures - **Effectiveness**: Demonstrated a 0.4% explanatory power in the Chinese market, indicating limited utility in normal conditions but significant value during extreme events[53] 2. Nonlinear Alpha Factors - **Effectiveness**: Not explicitly quantified but emphasized as a critical area for future development and differentiation in quantitative strategies[53][56]