Core Insights - The report indicates that the equity market is currently in a large-cap style, with a focus on valuation recovery in the short term (Q1 2025), suggesting a preference for investing in the CSI 300 ETF or CSI 300 index funds, while maintaining a balanced allocation in other index funds [2][6]. Group 1: Style Rotation Model Overview - The report introduces a multi-level monitoring model developed by the research team to capture signals of style rotation between large-cap and small-cap stocks [5]. - The first level of monitoring uses the one-month return difference between the CSI 800 large-cap index and the CSI 2000 small-cap index as an indicator of relative strength [5]. - The second level involves weekly tracking of the net value trends of the market capitalization factor from the MSCI Barra risk model to confirm style rotation signals [5]. - The third level combines fast and slow variable trend analysis to further validate the signals of style rotation [5]. Group 2: Performance Review of Style Rotation Model - The report reviews the performance of the style rotation model, showing that the CSI 300 index had a cumulative return of 11.07% over three months, with a Sharpe ratio of 2.90 [7]. - The CSI 500 index had a cumulative return of 13.00% with a Sharpe ratio of 1.94, while the CSI 1000 and CSI 2000 indices had lower cumulative returns of 10.29% and 3.52%, respectively [7]. Group 3: Signal Confirmation of Style Rotation - The model indicates a shift towards a large-cap style as of December 27, 2024, with the large-cap style expected to continue [15]. - The report provides a table of signal indicators showing the performance of large-cap versus small-cap indices over time, confirming the transition to a large-cap style [12][15]. Group 4: Fundamental Analysis - The report highlights that the CSI 300 index has the highest average net profit growth of 3.48% year-on-year compared to the CSI 500 (0.4%) and CSI 1000 (-7.7%) [27]. - The CSI 300 is identified as the preferred investment choice based on both fundamental and valuation analyses, with a focus on its strong performance metrics [27][28]. Group 5: Valuation and Market Sentiment - The report notes that as of January 17, 2025, the dividend yield of the CSI 300 index is at a high percentile, indicating a favorable investment environment [30]. - The analysis of trading volume and market sentiment suggests that the large-cap style is likely to perform well in the upcoming quarter, reinforcing the preference for the CSI 300 index [35].

Market Overview - No mainstream commodities reached new highs this week, while several agricultural products like soybeans and soybean meal hit one-year lows[4] - The palm oil market saw a significant drop in volume, while canola meal experienced a rise in volume[28] Macroeconomic Insights - Domestic policies since September have improved expectations, while Trump's trade policies continue to pose uncertainties for commodities in the medium to long term[5] - Economic data for November showed mixed results, with durable goods consumption supported by "trade-in" policies, while non-durable goods consumption declined[6] Investment Recommendations - Precious metals remain a long-term allocation target to hedge against currency credit risks, with gold expected to outperform silver in the near term[7] - Basic metals like copper, aluminum, and zinc are expected to experience supply disruptions, with a medium to long-term upward trend anticipated[7] - The black metal sector is expected to stabilize as domestic demand improves, with a potential trend shift anticipated before the Two Sessions in March[7] Commodity Performance - The week saw significant declines in agricultural products, with palm oil down by 6.5% and live pigs down by 7.5%[11][49] - The overall commodity market sentiment remains subdued, with many agricultural products facing trading difficulties due to weak demand expectations[13] Risk Factors - Key risks include the potential for the U.S. economy to weaken unexpectedly, slower-than-expected fiscal progress, and financial system panic[21]

Group 1: China Macro Policy Insights - Incremental monetary policy measures include a 50bps reduction in existing mortgage rates and a decrease in the down payment for second homes to 15%[7] - A total of 300 billion yuan has been allocated for housing refinancing, with the support ratio increased from 50% to 100%[7] - The government has introduced a special bond program to support stock buybacks, exceeding market expectations[7] Group 2: Economic Indicators - China's GDP growth for Q3 2024 is reported at 4.6%, slightly below the previous quarter's 4.7%[20] - The retail sales growth in September 2024 reached 3.2%, surpassing the expected 2.5%[20] - Exports in September 2024 amounted to 2.17 trillion yuan, marking a 6.2% year-on-year increase, the highest in the last decade[20] Group 3: U.S. Economic Outlook - The U.S. economy is showing signs of a soft landing, with unemployment rates and job performance exceeding market expectations[11] - Inflation remains a key concern, with the CPI's downward trend halting, indicating potential risks of rising inflation[11] - The market anticipates a 25bps interest rate cut in November 2024, influenced by strong economic data[25] Group 4: Global Economic Context - Global PMI indicators are predominantly below the growth line, while inflation continues to decline[24] - The U.S. fiscal deficit has expanded, with interest costs surpassing military spending, highlighting fiscal pressures[24] - Emerging markets are expected to recover, particularly in Mexico, while India and Russia show neutral growth prospects[32]

期货研究报告|宏观研究 专题报告：失业与就业 ·研究员-赵嘉瑜·联系电话：13686866941·联系人：王昊昇-18674061227 2024年08月9日 ·zhaojiayu@cmschina.com.cn·执业资格号:Z0016776 | --- | --- | --- | |----------|-------|-----------------| | | | 01 引言 | | | | | | 目录 | | 02 失业的衡量 | | contents | | 03 失业的类型 | | | | 04 应用 | CMF ூ 招商期货 | --- | --- | --- | --- | |----------|-------|-------|-----------------| | | | | 01 引言 | | 目录 | | | 02 失业的衡量 | | contents | | | 03 失业的类型 | | | | | 04 应用 | 短期经济波动：总供给与总需求 让学员理解短期经济波动的现象，并从总供给和总需求的角度讲解短期经济波动。 短期经济波动：经济波动机制、货币和财政政策 主要是讲解货币、财 ...

期货研究报告 | 宏观研究 专题报告：四个企稳迹象 2024年07月31日 ·研究员-赵嘉瑜 ·联系电话：13686866941 · zhaojiayu@cmschina.com.cn ·执业资格号: Z0016776 2024年07月31日 商品市场的四个企稳迹象 5月底以来的下跌交 易逻辑扭转 价格有底部支撑 中国：低内需预期→政策加码预期 欧洲：短期经济扰动→中期复苏前景 美国："特朗普交易"降温 商品市场 企稳回升 金工指标提示拐点到来 商-股共振向上 数据来源：招商期货 2 商品市场的企稳迹象 5月底我们成功预测到了商品趋势的逆转，而近期我们观察到了商品市场的企稳迹象。 ➢ 过去一个月，商品市场在交易什么？美国-"特朗普2.0"、中国-内需疲弱、欧洲-复苏不及预期，但目前这三 点都出现了改善的迹象。 ➢ 目前商品价格估值较低，悲观情绪已充分释放。 ➢ 更长周期看，全球制造业上升期即将到来； ➢ 股市情绪已经见底，股-商共振会引导商品企稳回升。 3.28 买国债传 3.31 PMI 大超预期 买卖国 债消息 落地 517新 政 531 PMI远不及 预期，央行说卖 国债 625 北京放政策 央行借券国 ...

Group 1: Market Overview - The Federal Reserve's interest rate hikes have ended, leading to a more relaxed global liquidity environment, which is beneficial for commodity markets[3] - Berkshire Hathaway holds $180 billion in cash, indicating a surplus of liquidity relative to quality assets, which often supports commodity prices[4] - Major economies are maintaining high debt levels, necessitating continued loose monetary policies, which could further support commodity demand[5] Group 2: Commodity Trends - Global copper inventories are at their highest levels since 2020, indicating potential supply pressures[45] - The LME copper market is experiencing its deepest contango since 2000, suggesting a bearish outlook in the short term[45] - The overall commodity market is expected to face short-term obstacles due to a lack of strong industrial demand and the delayed onset of a global easing cycle[84] Group 3: Economic Indicators - The PMI index showed unexpected improvement at the end of March, which laid the groundwork for a commodity price increase in the following months[73] - Industrial profits in China need to improve significantly to strengthen the current inventory replenishment cycle[23] - The global manufacturing PMI has shown an upward trend, indicating a potential recovery in industrial activity[14]

The provided content does not include any quantitative models or factors related to the task requirements. The document primarily discusses climate change, its impact on agriculture and energy, and market dynamics in the carbon and electricity sectors. There are no mentions of quantitative models, factor construction, or backtesting results.

Quantitative Models and Construction Methods 1. Model Name: Self-developed Price-Volume Model - **Model Construction Idea**: The model is designed to assess the short-term trend sustainability and potential reversal risks in the commodity market by analyzing price and volume data[28] - **Model Construction Process**: The model evaluates two key indicators: 1. **Market Trend Smoothness**: This measures the smoothness of price trends across various commodities. When the smoothness indicator reaches historical highs, it suggests that most commodities have extended trends and are at risk of trend reversal. 2. **Market Expectation Degree**: This measures the degree to which market prices are driven by expectations or sentiment rather than fundamental factors. A high expectation degree indicates that prices are primarily sentiment-driven, increasing the risk of trend reversal if market sentiment changes. Both indicators are calculated using historical data and are benchmarked against their historical distributions to identify extreme values[28][30][32] - **Model Evaluation**: The model effectively identifies extreme market conditions, providing valuable insights for risk management and allocation adjustments[28][30] --- Model Backtesting Results 1. Self-developed Price-Volume Model - **Market Trend Smoothness**: The indicator is currently near its historical maximum, signaling a high risk of trend reversal[30] - **Market Expectation Degree**: The indicator is also at a historically high level, suggesting that current price levels are heavily influenced by market sentiment rather than fundamentals[32] --- Quantitative Factors and Construction Methods 1. Factor Name: Commodity Index/CTA Long-Term Ratio - **Factor Construction Idea**: This factor measures the relative performance of the commodity index compared to long-term CTA strategies, providing insights into allocation preferences under different market conditions[9][12] - **Factor Construction Process**: The ratio is calculated as: $ \text{Commodity Index/CTA Long-Term Ratio} = \frac{\text{Commodity Index Value}}{\text{CTA Long-Term Strategy Index Value}} $ Historical data from 2019 to 2024 is used to analyze the ratio's trends and identify key phases of performance divergence between the two[9][12][35] - **Factor Evaluation**: The factor highlights the complementary nature of commodity indices and CTA strategies, with indices performing better in bull markets and CTAs excelling in bear markets[9][12] --- Factor Backtesting Results 1. Commodity Index/CTA Long-Term Ratio - **Phase I (2019/1/2 - 2019/12/27)**: Ratio increased by 12%[35] - **Phase II (2020/4/3 - 2020/9/4)**: Ratio increased by 13%[35] - **Phase III (2020/9/25 - 2021/5/7)**: Ratio increased by 26%[35] - **Phase IV (2021/11/5 - 2022/3/25)**: Ratio increased by 19%[35] - **Phase V (2022/7/15 - 2023/3/3)**: Ratio increased by 31%[35] - **Phase VI (2023/5/26 - 2024/5/17)**: Ratio increased by 19%[35]

期货研究报告 | 金工研究 2024 年06 月11 日 金融工程专题报告 相对 2020 年和 2021 年的高光表现，商品 CTA 度过了近两年的调整期。尽管自 3 月份至今 CTA 迎来一波不错的净值修复，但市场的疑虑依然存在。通过分析 CTA 近两年调整原因并结合宏观研判我们得到了以下结论： ❑ 风险提示： 相关报告 2040529 招期策略专题报告：期 货市场分析及私募业绩归因-赵 嘉瑜 研究员：赵嘉瑜 (+86)13686866941 zhaojiayu@cmschina.com.cn F3065666 Z0016776 联系人：乔垒 (+86)15805605265 qiaolei1@cmschina.com.cn F03109207 专题报告 CTA策略整装再出发 | 图 | 1：不同类型 CTA 指数的净值走势 | 4 | | --- | --- | --- | | 图 | 2：量价类因子的净值表现 | 5 | | 图 | 3：中短周期 CTA 与日成交额的对比 | 5 | | 图 | 4：中短周期 CTA 与品种日内波动性对比 | 6 | | 图 | 5：中长周期 CTA 与长周期波动率的 ...

上证指数 深证成指 创业板综 科创50 上证50 沪深300 中证500 中证1000 增量资金进场 市场突破上行 • 研究员-于虎山 • 联系电话：0755-82709642 2024年5月16日 01 宏观经济与政策环境 01 宏观经济与政策环境 30.00 35.00 40.00 45.00 50.00 55.00 60.00 65.00 70.00 2022/04 2022/10 2023/04 2023/10 2024/04 PMI 月 财新中国PMI 月 01 宏观经济与政策环境 中国:PMI:新出 口订单 中国:PMI:产成 品库存 中国:PMI: 进口 中国:PMI:主要原材 料购进价格 中国:PMI:从 业人员 指标名称 中国:PMI: 生产 资料来源：WIND，招商期货 资料来源：WIND，招商期货 上证指数 1 0.883 0.607 0.825 0.897 0.958 0.921 0.652 科创50 0.825 0.946 0.76 1 0.67 0.839 0.928 0.737 中证500 0.921 0.963 0.772 0.928 0.695 0.866 1 0.805 3 ...