中信证券:AI重构证券投资决策入口 从信息展示走向任务执行与资产经营 中信证券研报称,证券AI应用正由早期的简单问答,转向系统性降低信息处理、研究比较、组合诊断和投后跟踪成本,推动证券平台由行情展示和交易执行入口向投资任务执行及资产经营平台演进。短期行业仍处于产品验证和场景渗透阶段,中长期竞争将由“能否接入模型”转向“能否稳定完成投资任务、嵌入高频工作流并形成商业闭环”。随着底层模型逐步基础设施化,行业壁垒将更多来自专业金融数据、投研流程产品化、高频用户入口、账户资产、产品供给和合规治理等复合能力,产业价值有望沿“投研任务入口—财富管理闭环—机构端基础设施”三条路径集中。投资策略方面,可围绕决策入口、资产闭环和机构基础设施三条主线配置。优先关注拥有高频投资任务入口、专业金融数据和工具编排能力的金融信息平台;关注能够把AI判断连接到证券账户和客户资产的财富管理闭环平台;最后建议关注受益于金融行业相关IT建设需求的金融IT公司和数…

Channel
股市宏观策略行业研报 A股票
@hgclhyyb
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
19,466subscribers
+733 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001551700031 |
|---|---|
| Type | Channel |
| Username | @hgclhyyb |
| Created | Between 1 August 2021 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 19 September 2026 |
| Measurements held | 31 |
| Confirmed unchanged | 1 time, most recently 19 September 2026 |
| On Telegram | t.me/hgclhyyb |
Topic
Crypto & trading — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 65% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 19 Sept 2026, 12:16 | 19,466 | +10 |
| 17 Sept 2026, 00:17 | 19,456 | +10 |
| 15 Sept 2026, 04:58 | 19,446 | +38 |
| 13 Sept 2026, 10:59 | 19,408 | +14 |
| 8 Sept 2026, 18:39 | 19,394 | +59 |
| 5 Sept 2026, 13:57 | 19,335 | +32 |
| 3 Sept 2026, 17:22 | 19,303 | +1 |
| 2 Sept 2026, 13:23 | 19,302 | +20 |
| 1 Sept 2026, 10:55 | 19,282 | +12 |
| 31 Aug 2026, 07:23 | 19,270 | +6 |
| 29 Aug 2026, 11:53 | 19,264 | +13 |
| 28 Aug 2026, 15:23 | 19,251 | +23 |
| 27 Aug 2026, 12:43 | 19,228 | +45 |
| 26 Aug 2026, 11:08 | 19,183 | +39 |
| 25 Aug 2026, 09:42 | 19,144 | +37 |
| 24 Aug 2026, 12:17 | 19,107 | +102 |
| 22 Aug 2026, 18:26 | 19,005 | +45 |
| 21 Aug 2026, 11:32 | 18,960 | +13 |
| 20 Aug 2026, 12:03 | 18,947 | +25 |
| 19 Aug 2026, 12:35 | 18,922 | first reading |
Engagement
669 posts held, back to 7 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 53 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.918%
- avg views ÷ 19,466 subscribers
- Avg views / post
- 179
- 204 posts measured
- Reaction rate
- 0.193%
- reactions ÷ views · ER floor
- Posts in window
- 204
- of 669 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 12 of 204 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 September 2026 |
|---|---|
| Posts held | 669 (7 August 2026 – 3 September 2026) |
| Views total | 36,461 |
| Reactions total | 9 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 01:18 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Reaction mix
36 reactions across 32 posts, in 3 distinct kinds. The most used accounts for 94.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 34 | 94.4% | |
| 👎 | 1 | 2.78% | |
| 🤡 | 1 | 2.78% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 49 of the 669 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 36 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 669 most recent posts we hold, published 7 August 2026 to 3 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
摩根士丹利 :新城控股估值存在明显低估 公募REIT潜在上市可为催化剂 摩根士丹利表示,新城控股当前估值明显低估了其流动性改善、业务及恢复分红的潜力,预计四季度公募REIT上市将成为重要催化剂,建议投资者继续增持。分析师Stephen Cheung等在报告中指出,新城控股管理层在业绩发布后的活动中释放出积极信号,包括住宅销售、购物中心租赁、再融资以及资产处置等方面的指引,这进一步增强了其对新城复苏前景的信心。随着流动性改善,公司有望恢复全年股息派发。公司目标为年底前完成首只公募REIT上市。对新城控股评级为“增持”,股价目标17.60元;该股昨日收报11.94元。
中信证券:视频模型竞争转向生产可用与商业兑现 AI剧成为率先形成规模消耗的应用场景 中信证券研报称,视频模型竞争正由效果比拼转向生产可用与商业兑现,AI剧成为率先形成规模消耗的应用场景。Seedance 2.5通过长时长生成、多模态参考和一致性编辑提高内容交付效率,番茄小说、创作者中心和制作机构承接IP开发与规模生产;红果则依托免费内容、算法分发及广告电商变现建立商业回收出口,并通过审核、分账与投资政策推动内容供给精品化,字节由此形成模型、内容、流量与变现相互协同的产业闭环。随着内容供给快速扩张和投流资源趋于稀缺,AI剧的核心矛盾已由生产能力不足转向有效供给不足,产业链价值有望进一步向具备高商业化效率、优质IP与精品制作能力、高质量语料资源,以及与红果深度合作的公司集中。
中信证券:维持今年9月美联储维持利率不变的判断 中信证券研报称,美国7月CPI环比增速录得0.1%,核心CPI环比为0.2%,均符合市场预期。7月美国CPI环比小幅上涨,主要由核心商品项环比反弹和核心服务项增速回升推动,同时能源价格连续第二个月下跌部分抵消了通胀上行压力。7月美国PPI同比增速延续回落,整体美国通胀预期上行风险可控。当前美伊冲突前景仍存在较大不确定性,原油价格、美国通胀压力上行风险尚存,但预计整体美国通胀压力可控,维持今年9月美联储维持利率不变的判断。
中金 财富期货:美国10年期国债收益率从盘中高位回落,黄金和美股也出现反弹行情 油价冲高回落后涨势暂歇,通胀预期随之降温。美国10年期国债收益率从盘中高位回落,黄金和美股也出现反弹行情。但是需要注意的事,“替代方案”的红海港口也被威胁,沙特原油出口暴跌,油价下行需要美伊之间达成一个较为靠谱的协议,否则地缘问题带来的通胀压力、债务风险等仍会反复扰动市场,建议耐心等待黄金调整结束。
【盘前题材挖掘】①印尼最大镍工业园或减产多达四成,镍价有望迎来反弹。②产业进入工程验证大年,可控核聚变进入快速发展期。③AI时代光网络硬件商或成最大赢家,机构称看好光通信板块反弹。 ①印尼最大镍工业园或减产多达四成,镍价有望迎来反弹。②产业进入工程验证大年,可控核聚变进入快速发展期。③AI时代光网络硬件商或成最大赢家,机构称看好光通信板块反弹。
中金 :看好AI算力集群持续扩容背景下光通信散热赛道的高成长性 中金公司研报称,看好AI算力集群持续扩容背景下光通信散热赛道的高成长性,建议重点关注光模块VC、液冷Cage及共封装交换机液冷机会。随着光模块速率升级,单模块功耗不断提升,传统风冷逐步接近散热边界,VC均热板、液冷cage等高效散热方案渗透率有望加速提升,行业同时受益于光通信需求增长的Beta和液冷渗透率、单位价值量提升的Alpha;同时,NPO\/CPO\/XPO等新封装路线演进有望进一步将散热需求由模块级向系统级延伸,持续打开产业空间。供应链层面,光模块散热厂商依托全球领先的光模块产业集群,在客户协同、快速响应、成本控制及精密制造方面具备优势,光模块cage厂商在风冷cage时代已切入海外头部连接器供应链,液冷时代有望沿用既有客户关系实现产品升级和价值量提升。
中金 :9月行业配置把握景气线索下的结构性机会 中金公司发布9月行业配置研报称,把握景气线索下的结构性机会:(1)科技成长后市或呈现分化走势,需要精挑细选:AI基础设施相关环节,如光通信、PCB等环节,高景气状态在今年确定性仍较强,超跌后有望出现反弹。半导体及算力等领域较多公司则仍需关注基本面与估值的匹配程度;创新药较多公司进入临床数据验证阶段,值得自下而上关注。(2)综合考虑地缘局势与产能周期位置,关注业绩向好及供需格局改善的领域:如工程机械、电网设备、石化化工等。纯内需行业的基本面回升进展仍然相对偏缓,需要进一步观察。
华泰证券:建议优先关注业绩能见度较高的方向 华泰证券发布策略研报称,资产配置上,市场正从扩张叙事转向兑现能力和盈利质量的再定价,短期流动性预期收紧可能压制估值,业绩真空期关注产业端是否有新的催化和订单验证,以及9月FOMC会议表态。建议优先关注业绩能见度较高的方向,如通信设备、半导体设备\/材料、PCB等,其次考虑AI应用的重估机会。
中信建投 :9月资产组合配置可围绕三条主线展开 中信建投研报称,9月资产组合配置可围绕三条主线展开,防御底仓:红利、高股息等低波动资产,对抗滞胀的黄金;结构性进攻:A股资源品和盈利确定性较强的硬科技;美股侧重点由拥挤的硬件瓶颈品种转向云厂商、软件应用、算力龙头和半导体设备。换言之,美元流动性敏感资产9月或有机会。谨慎配置:不追涨中国长久期债券,谨慎看待内需增长板块的做多空间。隐含的配置优劣排序:黄金、铜及资源红利资产优先;美股软件应用、云厂商和算力设备次之;债券中的长债,股票中的内需消费,大宗里面的铝偏谨慎。
中信建投 :电力设备及新能源行业景气兑现但估值压低 寻找需求的积极变量 中信建投研报称,二季度锂电储能在收入端兑现高景气,海风、光伏下挫反映行业目前在底部徘徊、电力设备行业也持续进入景气周期,特别是出口链表现较为出色,但对于未来的担忧压低了板块的估值。扩产层面,行业整体依然温和。投资建议:大储、户储板块、锂电及材料在二季度开始业绩增长兑现,供需形势依然良好,近期受到外部环境变化挑战,估值水平明显回落,值得继续重点关注。在订单或边际变化定价的范式上,重点关注国产燃气轮机产业链、AIDC、欧洲海风等环节公司订单变化。
摩根士丹利 :银行跻身亚洲人工智能受益行列 摩根士丹利表示,在亚洲人工智能应用推广、应对人口老龄化两大核心趋势下,银行属于净受益行业。股票策略师丹尼尔・布莱克(Daniel Blake)与乔纳森・加纳(Jonathan Garner )在一份客户研报中援引摩根士丹利构建的模型称,中国香港和新加坡的银行同时受这两大核心趋势的影响程度最高。报告指出,这些银行将受益于人工智能投资超级周期,同时也会受益于财富管理格局变化以及人口老龄化带来的人口结构转变。根据摩根士丹利的模型,汇丰、星展、华侨银行、渣打银行以及大华银行均具备较高的受益敞口,但策略师对澳大利亚银行持谨慎态度,原因在于其估值偏高、货币政策或将收紧,以及税收政策的不利调整。
Showing the 12 most recent of 669 posts we hold for @hgclhyyb. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
@jin10light · 25,121
Telegram ranks this channel #62 of 78 here — alongside 77 others — read 3 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 19 September 2026 — this entry's latest reading, not the date you are reading this.
“股市宏观策略行业研报 A股票” (@hgclhyyb), 19,466 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/hgclhyyb.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.