[Table_Page] 投资策略周报|农林牧渔 证券研究报告 [TAblE_TitlE] 农林牧渔行业 本周猪价小幅上行,水产复苏趋势延续 [TAblE_SummAry] 核心观点: 畜禽养殖:据搜猪网,7月12日,全国瘦肉型生猪出栏均价18.77元/公 斤,环比上周上涨1.40%,同比上涨8.75%。前期产能去化效应显现, 本周猪价继续上行。随着后续供给下降以及需求季节性回暖,3季度猪 价有望继续上行。从生猪公司的中报预告情况来看,2季度业绩基本均 实现扭亏,养殖成本处于改善过程中。展望3季度,养殖成本仍具有下 降潜力,生猪企业有望充分受益猪价上行与成本下行之间"剪刀差"扩 大,整体盈利水平有望超出市场预期。当前行业资产负债率整体处于高 位,预计后续产能恢复速度或较为缓慢。根据Mysteel数据,6月能繁母 猪存栏量环比增长0.37%,环比增幅收窄。当前板块估值再次回落至相 对低位,大型养殖企业重点推荐温氏股份、牧原股份,关注新希望,中 小养殖企业建议关注唐人神、天康生物、华统股份以及川渝生猪龙头企 业。白羽鸡方面,伴随消费旺季逐步到来,据Wind,本周商品代鸡苗和 毛鸡价格开启反弹,分别环比上涨12.8 ...

[Table_Page] 投资策略周报|基础化工 证券研究报告 [Table_Title] 基础化工行业 24Q2 龙头业绩拐点已现,关注美联储降息升温 [Table_Summary] 核心观点: ⚫ 行业基础数据跟踪:据 wind 资讯,7 月 8 日~7 月 12 日,SW 基础化 工板块上涨 1.75%,跑输万得全 A 指数 0.08pct;化工子行业下跌较 多,表现较差的有油气开采、钾肥和氟化工等板块,表现较好的有炭 黑,氨纶,锦纶等板块。 ⚫ 化工品价格下跌较多: 据百川、wind 资讯,在我们跟踪的 336 个产品 中,上涨、持平、下跌的产品数量分别为 67 种、164 种、105 种,占比 分别为 20%、49%和 31%。化工品价格下跌较多。价格涨幅前五: CCMP、醋酸、硫酸、烟煤、120#溶剂油。价格跌幅前五:液氯、硝磺 草酮、聚四氟乙烯 PTFE、异丁醛、工业磷酸一铵。 ⚫ 24Q2 化工行业龙头标的业绩拐点已现。化工行业龙头标的业绩拐点已 现。根据 WIND 资讯,以申万化工一级行业为基础,截至 2024 年 07 月 12 日,化工行业有 131 家 A 股上市公司公布了 2024 ...

[Table_Page] 投资策略周报|建筑材料 证券研究报告 [Table_Title] 建筑材料行业 [Table_Gr ade] 行业评级 持有 前次评级 持有 6 月社融符合预期,淡季水泥价格继续推涨 报告日期 2024-07-14 [Table_Summary] 核心观点: ⚫ 地产政策密集发布,市场预期有所修复,二手房成交环比改善、新房成 交降幅环比收窄,尽管目前地产链建材基本面受地产景气影响仍在左 侧,需等待地产企稳,但优质龙头企业仍表现出较强的经营韧性,如二 手房和存量房翻新需求支撑下零售建材韧性强、水泥和玻璃龙头持续 保持盈利领先优势。建议继续关注政策催化下建材修复机会,同时关注 底部涨价的水泥和部分结构性景气赛道(玻纤、出海、药玻等)。 ⚫ 消费建材:地产仍在寻底,龙头公司经营韧性强。消费建材长期需求稳 定性好(受益存量房需求)、行业集中度持续提升、竞争格局好的优质 细分龙头中长期成长空间仍然很大。2024 年地产仍在寻底,新开工面 积预计回落至中期较低水平,地产政策转变有望先带来销售面积好转; 核心龙头公司盈利领先地产行业实现有韧性的复苏。看好三棵树、兔宝 宝、北新建材、伟星新材、中国联 ...

Group 1: Polling Data - After the first debate, Trump's polling advantage has widened significantly, with his support in key swing states showing a clear lead over Biden[6] - In the latest polls, Trump's support in seven swing states is notably higher, with five states showing substantial leads over Biden[20] - Biden's job approval rating remains low, with a disapproval rate of 60% as of June 28, 2024[19] Group 2: Election Dynamics - The first debate has negatively impacted Biden's campaign, with his winning probability dropping from 45.0% on June 26 to 30.0% by June 29[33] - The upcoming election is likely to be a rematch between Trump and Biden, following their overwhelming victories in their respective party primaries[10] - Key issues for voters in swing states include the economy and inflation, with many expressing dissatisfaction with Biden's handling of these matters[49] Group 3: Economic Policies - Trump's economic policies during his term included significant tax cuts, with the corporate tax rate reduced from 35% to 21%[68] - Biden's proposed tax increases aim to raise the corporate tax rate from 21% to 28% and restore the top personal income tax rate from 37% to 39.6%[81] - Both candidates advocate for tariffs on Chinese imports, with Trump suggesting a baseline tariff of 10% on all imports[106]

Quantitative Models and Construction Methods Model Name: Large Order Ratio Factor - **Construction Idea**: The factor is based on Level 2 tick-by-tick order data, focusing on the ratio of large orders to total orders[2][10][24] - **Construction Process**: - Aggregate tick-by-tick order data to reflect the original order size[24] - Define large orders as those with transaction volumes greater than the mean plus N standard deviations[27] - Construct large buy order ratio factors (BigBuy_1p0, BigBuy_1p5, BigBuy_2p0) and large sell order ratio factors (BigSell_1p0, BigSell_1p5, BigSell_2p0) using different standard deviation thresholds[27] - Formula: $ \text{BigBuy}_1p0 = \frac{\text{Large Buy Orders}}{\text{Total Orders}} $[27] - **Evaluation**: The factor shows significant performance in predicting stock returns, especially in short-term trading windows[28][30] - **Test Results**: - 5-day window: RankIC mean 5.4%, win rate 64%, annualized return 33.15%, max drawdown 13.43%, Sharpe ratio 1.83[31] - 20-day window: RankIC mean 7.9%, win rate 70%, annualized return 28.08%, max drawdown 9.18%, Sharpe ratio 1.80[33] Model Name: Time-Dimension Decoupled Large Order Ratio Factor - **Construction Idea**: Decouple large order ratio factors based on different time periods within the trading day[10][38] - **Construction Process**: - Define large orders within specific time windows (e.g., first 15 minutes, first 30 minutes, last 15 minutes, last 30 minutes)[38] - Construct factors such as BigBuy_1p0_09301000 for large buy orders in the first 30 minutes[38] - Formula: $ \text{BigBuy}_1p0_09301000 = \frac{\text{Large Buy Orders (09:30-10:00)}}{\text{Total Orders}} $[38] - **Evaluation**: Time-dimension decoupled factors provide more stable returns and lower drawdowns compared to non-decoupled factors[40][42] - **Test Results**: - 5-day window: RankIC mean 3.4%, win rate 63%, annualized return 29.78%, max drawdown 13.02%, Sharpe ratio 1.63[44] - 20-day window: RankIC mean 4.5%, win rate 70%, annualized return 26.63%, max drawdown 8.37%, Sharpe ratio 1.73[48] Model Name: Order-Dimension Decoupled Large Order Ratio Factor - **Construction Idea**: Decouple large order ratio factors based on the buy and sell attributes of orders[10][56] - **Construction Process**: - Define factors based on combinations of large and small buy and sell orders (e.g., BigBuy_BigSell_1p0, BigBuy_SmallSell_1p0)[56] - Formula: $ \text{BigBuy_BigSell}_1p0 = \frac{\text{Large Buy Orders + Large Sell Orders}}{\text{Total Orders}} $[56] - **Evaluation**: Order-dimension decoupled factors show improved performance in multi-directional trading strategies[57][60] - **Test Results**: - 5-day window: RankIC mean 6.7%, win rate 72%, annualized return 31.01%, max drawdown 15.44%, Sharpe ratio 1.67[60] - 20-day window: RankIC mean 9.8%, win rate 82%, annualized return 28.57%, max drawdown 11.53%, Sharpe ratio 1.80[62] Model Name: Multi-Dimension Decoupled Large Order Ratio Factor - **Construction Idea**: Combine time and order dimension decoupling to construct more refined large order ratio factors[10][68] - **Construction Process**: - Define factors based on both time and order attributes (e.g., BigBuy_BigSell_1p0_09301000, BigBuy_BigSell_1p0_14301457)[68] - Formula: $ \text{BigBuy_BigSell}_1p0_09301000 = \frac{\text{Large Buy Orders + Large Sell Orders (09:30-10:00)}}{\text{Total Orders}} $[68] - **Evaluation**: Multi-dimension decoupled factors provide the most stable and high-performing returns across different market conditions[69][71] - **Test Results**: - 5-day window: RankIC mean 3.3%, win rate 66%, annualized return 29.02%, max drawdown 14.70%, Sharpe ratio 1.56[72] - 20-day window: RankIC mean 4.9%, win rate 75%, annualized return 26.56%, max drawdown 9.82%, Sharpe ratio 1.68[76] Model Backtest Results Large Order Ratio Factor - **5-day window**: RankIC mean 5.4%, win rate 64%, annualized return 33.15%, max drawdown 13.43%, Sharpe ratio 1.83[31] - **20-day window**: RankIC mean 7.9%, win rate 70%, annualized return 28.08%, max drawdown 9.18%, Sharpe ratio 1.80[33] Time-Dimension Decoupled Large Order Ratio Factor - **5-day window**: RankIC mean 3.4%, win rate 63%, annualized return 29.78%, max drawdown 13.02%, Sharpe ratio 1.63[44] - **20-day window**: RankIC mean 4.5%, win rate 70%, annualized return 26.63%, max drawdown 8.37%, Sharpe ratio 1.73[48] Order-Dimension Decoupled Large Order Ratio Factor - **5-day window**: RankIC mean 6.7%, win rate 72%, annualized return 31.01%, max drawdown 15.44%, Sharpe ratio 1.67[60] - **20-day window**: RankIC mean 9.8%, win rate 82%, annualized return 28.57%, max drawdown 11.53%, Sharpe ratio 1.80[62] Multi-Dimension Decoupled Large Order Ratio Factor - **5-day window**: RankIC mean 3.3%, win rate 66%, annualized return 29.02%, max drawdown 14.70%, Sharpe ratio 1.56[72] - **20-day window**: RankIC mean 4.9%, win rate 75%, annualized return 26.56%, max drawdown 9.82%, Sharpe ratio 1.68[76] Selected Large Order Factor Portfolio Performance All Market - **Annualized Return**: 36.61%[89] - **Max Drawdown**: 17.52%[89] - **Sharpe Ratio**: 2.03[89] - **Excess Annualized Return**: 33.07%[89] CSI 300 - **Annualized Return**: 12.24%[97] - **Max Drawdown**: 14.51%[97] - **Sharpe Ratio**: 0.75[97] - **Excess Annualized Return**: 13.40%[97] CSI 500 - **Annualized Return**: 22.55%[103] - **Max Drawdown**: 9.08%[103] - **Sharpe Ratio**: 1.12[103] - **Excess Annualized Return**: 18.67%[103] CSI 800 - **Annualized Return**: 18.54%[114] - **Max Drawdown**: 7.22%[114] - **Sharpe Ratio**: 1.14[114] - **Excess Annualized Return**: 18.95%[114] CSI 1000 - **Annualized Return**: 24.61%[123] - **Max Drawdown**: 10.43%[123] - **Sharpe Ratio**: 1.36[123] - **Excess Annualized Return**: 17.39%[123] ChiNext - **Annualized Return**: 36.20%[131] - **Max Drawdown**: 25.15%[131] - **Sharpe Ratio**: 1.59[131] - **Excess Annualized Return**: 25.07%[131]

Xml [Table_Page] 投资策略周报|国防军工 证券研究报告 [Table_Title] 国防军工行业 中航电测重组过会,看好板块中长期景气度 [Table_Summary] 核心观点: 中航电测百亿重组过会,中国核电拟定增募资不超 140 亿元,看好板 块中长期确定性和景气度。7 月 11 日,中航电测发布公告向航空工业 集团发行股份购买其持有的成都飞机工业(集团)有限责任公司 100% 股权并购事项过会,交易金额 174 亿元。据北京商报,上述并购系注 册制以来交易金额最高、规模最大的深市重组项目。7 月 11 日,中国 核电公告拟向控股股东中核集团和战略投资者社保基金会发行 A 股股 票,其中中核集团拟认购 20 亿元,社保基金会拟认购 120 亿元。募 集资金总额不超 140 亿元,将用于辽宁徐大堡核电站、福建漳州核电 站和江苏田湾核电站等项目。 新质生产力方向,船厂生产经营数据同比改善明显,船舶景气度持续 向上,中国船舶、中国动力 24H1 业绩同比改善明显。航空出海、大 飞机、低空经济等进展持续更新。7 月 12 日,据"中国船舶报"公众 号,2024 年上半年,上海三大央企船厂江南造船 ...

识别风险,发现价值 请务必阅读末页的免责声明 1 / 28 [Table_Page] 跟踪分析|房地产 证券研究报告 [Table_Title] 房地产及物管行业 24 年第 28 周周报 保障房再贷款推进,7 月新房成交同比有望转正 [Table_Summary] 核心观点: ⚫ 本周政策情况:保障房再贷款推进,地方探索小宗地块开发。近期租赁 住房贷款及保障性住房再贷款持续推进,截至 Q2 末,金融机构已发放 近 250 亿元租赁住房贷款,央行已审核发放再贷款超 120 亿元。本周 地方政策调整相对较小,广州港澳台及外籍人士限购政策跟进放松,昆 明、宁波等地认房认贷标准边际松动,贵州瓮安县探索小宗地块开发。 ⚫ 本周基本面情况:新房成交季节性回落,二手房热度稳定维持高位。 据 Wind 及克尔瑞,本周 52 城新房成交面积 356 万方,环比下降 47%, 同比下降 13%,本周新房成交热度季节性回落,7 月前 11 天同比下降 5%,7 月成交同比有望转正。二手房方面,本周 13 城网签口径成交 170 万方,环比下降 13%,同比上升 38%,74 城认购口径日均成交 2029 套,环比下降 0.3%, ...

[Table_Page] 投资策略周报|煤炭开采 证券研究报告 [Table_Title] 煤炭行业周报(2024 年第 28 期) 煤价稳中有升,中报预告短期承压,Q3 有望延续恢复 [Table_Summary] 核心观点: ⚫ 近期市场动态:动力煤价小幅上涨,双焦价格保持平稳。根据汾渭能 源,动力煤方面,CCI5500 大卡煤价 7 月 12 日最新报价 856 元/吨, 周环比上涨 9 元/吨。年度长协 7 月港口 5500 大卡煤价为 700 元/吨, 环比持平。本周港口和产地煤价小幅上涨,临近周末价格趋稳。近期随 着各地相继出梅,江南、华南等地出现高温天气,电厂日耗回升,市场 交易情绪改善。预计随着气温继续升高,以及贸易商和电厂库存消耗, 煤价有望逐步企稳回升。下半年煤价支撑主要来自:(1)国内供给 5 月 以来虽有恢复,同比仍延续下降;(2)下半年旺季需求支撑明显;(3) 库存对煤价的压制有望缓解。焦煤方面,本周国内焦煤市场价格保持 平稳。需求端,6 月下旬下游焦炭价格提涨 50 元/吨,目前产业链处于 需求淡季,但焦企开工积极性较高,铁水产量也维持相对高位,焦煤采 购维持刚需。供给端,上半年山 ...

Xml [Table_Page] 投资策略周报|传媒 证券研究报告 [Table_Title] 互联网传媒行业 分众与美团将合作加强低线城市梯媒运营,关注暑期档内容供给拐点 [Table_Summary] 核心观点: ⚫ 本周(7月8日-7月12日)中信传媒板块下跌2.64%,跑输上证综指3.37 个百分点。本周(7月8日-7月12日)A股传媒板块行情回调,主要由 于板块缺少基本面改善预期或AI等方向短期主题催化等。展望后市, 我们建议把握两条主线:一是优选业绩较好的板块和优质公司,业绩 落地验证基本面后,有望支撑估值的稳步抬升,重点可关注互联网、 游戏以及长视频、营销等板块。二是持续跟踪板块内AI应用的边际变 化,有望提升市场对AI应用的落地预期。建议关注有AI产品或技术布 局、正在持续推进落地的公司。另外,也可以关注部分账上现金充足、 股息率具备吸引力、且积极拓展新业务或有新业务布局预期的公司。 ⚫ 投资建议:建议重点关注平台经济业绩及估值双修复机会,以及AI+及 数字经济机会。(1)互联网方面,建议关注:腾讯、美团(到店格局 稳定后带来的UE优化)、快手(利润释放超预期等因素)、哔哩哔哩 (财务改善)、 ...

社保参与核电定增,火电有望柳暗花明 [Table_Summary] 核心观点: ⚫ 关注:中广核电力+浙能电力+华润电力+广州发展+华能国际电力股份+ 华电国际电力股份+国电电力+长江电力+国投电力 ⚫ 中报业绩预告陆续出炉,水电高增如期兑现、火电风电电量下滑。纵览 中报业绩预告及经营数据,我们认为有几点值得关注:(1)水电发电量 高增得到数据验证,如长江电力 Q2 同比+43%、桂冠电力 Q2 业绩预 告中枢同比+57%,我们预计水电低基数效应预计仍将延续;(2)火电 发电量受水电挤压较为明显,如国电电力 Q2 火电发电量下滑 7%、粤 电力下滑达到 16%,从业绩层面来看,皖能电力以业绩预告中枢计算 同比增长 19%,国电电力、大唐发电、中国电力等公司业绩高增但均有 水电业务影响;(3)风电发电量下滑明显,如龙源电力 Q2 下滑 6.4%, 华润电力下滑 2.4%、光伏普遍受装机增长影响发电量高增。总的来说, 水电火电明显互补的状态表现突出,预计三季度将有所缓和。 ⚫ 逻辑未变、节奏扰动,火电终将柳暗花明。本周火电波动较大,主要系 临近业绩期市场担忧火电发电量承压。我们再度梳理行情演绎思路: (1)逻辑未 ...