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]

价格传导不畅削弱修复成色–2024 年 5 月中 [★Ta5b月le_经Su济m数m据ary解] 读： 3、需求端方面，大规模上设备更新、消费品以旧换新、电商 618 股 指 期 货 大促等成为结构性支撑点。商品零售销售有所修复；制造业投 资增速上行 0.1%至 9.4%。但基建投资仍受制于财政节奏，以及 地产投资仍在继续寻底。房价加速下行，地产政策宽松效果仍 待观察。 中国经济修复不及预期，美国降息预期波动，海外地缘政治风 扫描二维码，微信关注"东证繁微"小程序 险。 热点报告——股指期货 [T走ab势le_评R级an：k] 股指：震荡 报告日期：2024年06月18日 2、生产端，5 月份工业增加值同比增速 5.6%，较前值回落 1.1%， 服务业生产指数同比增速 4.8%，较前值扩张 1.3%。服务业修复 态势好于工业。 5 月份中国经济修复仍保持了一个缓步向前的态势，上行斜率仍 旧偏低。并且当前最突出的问题在于居民资产负债表修复缓慢， 预期低迷、收入减少、消费支出下沉，进而导致国内价格传导 机制不畅，上游涨价对下游的传导严重被削弱，进一步蚕食了 中下游行业利润率修复的空间。大规模设备更新以及消费品依 ...

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 06 月 16 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(3.2%)，科创 50(2.2%)，中证 2000(2.1%)，标 普 500(1.6%)，北证 50(1.6%)；本周涨跌幅排名后五的宽基指数 及其涨跌幅分别为恒生指数(-2.3%)，小盘价值(-2.0%)，中盘价 值(-2.0%)，大盘价值(-1.4%)，上证 50(-1.3%)；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(5.7%)，标普 500(2.9%)，科创 50(1.5%)，胡志明股市指数(1.4%)，日经 225(0.8%)；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(-5.1%)，北证 50(-3.4%)，小盘价值(-3.3%)，中证 1000(-3.3%)，中盘价值(-2.6%)。 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 别为通信(6.0%)，电子(4.7%)，计算机(3.7%)，传媒(2.1%)，汽车 (1.3 ...

周度报告-FOF 研究 各策略收益下滑，主观表现优于量化 [报Ta告bl日e_期Ra：nk] 2024 年 05 月 22 日 ★本周市场回顾：（05.13-05.17） 股票市场，各大主要指数多数收跌，沪深 300 周度收益为 0.32%， 较之于中小盘的-0.79%和-0.19%的跌幅较大。本周各大类风格因 子涨跌参半，其中账面市值比和盈利率因子录得显著正收益， 剩余因子中贝塔因子和成长因子的跌幅最大。 商品市场大幅收涨，南华综合指数 2.02%，风格因子方面，本周 因子均收跌，波动率因子和流动性因子的跌幅最显著，其余因 子唯对冲压力因子的涨幅较显著。 ★主要策略表现及配置建议： FOF 研 究 各策略收益均下滑。量化多头策略，在跟踪 500 和 1000 指增管 理人普遍录得正超额，相较前一周有所提升，300 指增管理人超 额分化。当前市场正在震荡反弹，阿尔法环境整体向好，但是 波动性有所增加。建议均衡配置，关注风控层面严格的管理人。 CTA 策略表现分化，主观 CTA 持续优于量化 CTA。在跟踪量化 CTA 涨跌参半，各周期下的管理人均表现分化，日内管理人相 对表现靠前，短周期和长周期相对好于中周期 ...