国航、东航、南航分别公告各自与空客签订96、100 架、 96 架A320NEO 系列飞机采购协议，总计292 架飞机采购协议；上 述飞机计划于2023 年至2027 年分批交付于各公司，主要起到存量 机型置换、补充运力作用。

航空股上涨的启动时点通常在暑运或春运来临前夕，5次上行阶段均为跨年度的上涨行情，历时7-31个月不等。航空指数随大盘震荡，具有明显的周期性，且震荡幅度大于沪深300，航空股适合周期投资。

Establishments described in this report are primarily participating in the space propulsion market. Spacecraft propulsion is any method used to accelerate spacecraft and artificial satellites. In-space propulsion exclusively deals with propulsion systems used in the vacuum of space and should not be confused with space launch or atmospheric entry.

The Global Innovative Markets Forecast report series by Perry/Hope Partners features market sales of thousands of high-tech products and services in various industries such as transportation, hardware, electronics, electrical products, printing services and food products. The reports are published annually based on a unique methodology that uses robust data sources and detailed logarithms to estimate global markets for manufactured products. The main steps in the methodology are: - Products and services definitions and historical data are primarily based on secondary data collected from Internet research which is updated annually. Data sources include trade association databases, trade journal articles, press releases, published research reports, and annual reports.

2022 年5 月，中证军工指数上涨9.6%（4 月指数下跌12.7%），跑赢大盘 7.8ppt；跑赢创业板5.9ppt。在经历了年初至4 月26 日的下跌后，随着年报和 季报披露，基本面逻辑再次强化，估值创历史新低后反弹修复，叠加国企改革催 化，行业重回上涨趋势。展望6 月，我们明确看好后续机会：1）行业需求确定， 且细分领域或有加速，在二季度体现更加明显；2）通胀及疫情等对行业影响较 小，比较优势凸显；3）估值修复尚未完成，当前PE/TTM 仍低于近3/5/10 年 中枢；4）国企改革等将对行业形成较强催化。

投资建议：持续推荐航空板块。我们认为行业属于典型困境反转框架下，具 备周期价格强弹性。1）航空供给确信趋紧，静待需求复苏，推升价格弹性。 我们研究预测23-24 年行业供给显著收缩，测算23 相比较19 年行业累计机队 规模扩张介于12%-21.5%，属于极低增速，而截至目前，航司仍未有明确订单 落地，考虑交付周期以及当前经营环境，或导致运力紧张进一步延续至2024 年。需求一旦恢复，行业有望实现供需反转，从而实现强价格弹性。2）前述 观察票价近期提升明显，鉴于样本时间尚短，我们建议持续关注，从中观测 是否可视为未来价格弹性的预演。随着22 夏秋新航季提价的陆续落地，国内 前30 大航线，已有20 条提价5 次及以上，我们预计一旦供需反转，本轮票价 弹性将超以往。 3）推荐节奏：大周期仍看好中国国航，近期建议尤其关注上 海主基地航司春秋、吉祥、以及支线市场龙头华夏航空。

Autonomy and artificial intelligence (AI) are, and will remain, the main drivers promoting commercial UAS adoption and associated market growth. Autonomous flight reduces the need for expensive manpower whereas AI-driven data collection and processing reduces the time it takes to produce results that directly impact decision-making.