海通国际_中国电子:DeepSeek-OCR2:以“因果阅读顺序”重塑复杂文档理解_20260129.pdf
摘要
文本

中国电子 China (A-share) Technology
DeepSeek-OCR2:以“因果阅读顺序”重塑复杂文档理解
DeepSeek-OCR 2: Rewriting Complex Document Understanding with Visual Causal Reading Order
姚书桥 Barney Yao
吕小潼 Xiaotong Lyu
barney.sq.yao@htisec.com
xt.lyu@htisec.com
Flash Analysis
(Please see APPENDIX 1 for English summary)
事件
2026年1月27日,DeepSeek团队正式发布研究论文《DeepSeek-OCR2:Visual Causal Flow》,并同步开源面向OCR与文档解析场景的专用模型 DeepSeek-OCR2(以下简称 DeepSeek-OCR2)。新版模型核心升级在于其视觉编码器 DeepEncoder V2的突破性改进,该设计使模型摆脱传统“自上而下、从左至右”的机械式扫描方式,转为依据文档结构特征与语义关联进行动态理解,实现了更贴近人类认知逻辑的图文、表格及公式解析能力,有望显著提升复杂文档处理的准确性与效率。
点评
这次升级抓住了文档理解里最难啃的一块一一复杂版式的阅读顺序。在复杂文档(如多栏排版、嵌套表格及公式混杂文本)的处理中,传统OCR及多数视觉语言模型常将图像中的“空间顺序”直接等同于“语义顺序”,导致识别结果出现串行、错位等问题。DeepSeek-OCR2针对这一核心瓶颈进行了关键改进:以轻量级语言模型Qwen2-500M替代原有的CLIP风格编码器,并引入具备因果注意力的“因果流查询”机制。该设计能够在编码阶段即对视觉token按内容逻辑进行重组,使其在进入解码器前已完成结构理顺,从而实现类似人类“先理解整体布局,再依序阅读内容”的认知过程,显著提升了模型对复杂版面的语义连贯性与识别准确率。
从公开指标看,它已经站进了第一梯队。在权威文档理解基准OmniDocBench v1.5的评测中,DeepSeek-OCR2的综合得分达到 91.09%,较上一代显著提升3.73个百分点;其反映阅读顺序准确性的编辑距离指标由0.085优化至 0.057,验证了其“按结构阅读”的技术路径在改善识别连贯性方面的有效性。横向对比来看,尽管当前在该榜单中略低于排名第一的PaddleOCR-VL(92.86%),但差距已收窄至较小区间,表明其整体性能已逼近行业领先水平。尤为值得关注的是模型效率:在同等视觉token预算(1120)条件下,DeepSeek-OCR2的文档解析编辑距离为0.100,优于Gemini3Pro的0.115(该指标数值越低性能越好),体现出其在保持高压缩率的同时并未牺牲识别质量,具备了出色的性能-效率平衡能力。
这个模型对产业落地的意义很直接:更低成本、更强文档解析能力。在性能表现上,该模型对复杂文档页面的处理仅需256至1120个视觉token,极高的信息压缩效率将显著降低下游大模型在处理PDF、扫描文件、财报、研报及合同等材料时的计算负载与处理时延。同时,该模型以Apache-2.0协议开源,参数量为30亿,适中的规模与友好的许可使其易于集成至企业现有流程,可广泛应用于PDF转Markdown、表格与公式结构化抽取、以及RAG知识库构建等场景。从生产环境反馈来看,其在实际线上日志图像与批量PDF处理任务中的文本“重复率”指标显著改善(例如分别从 6.25%下降至 4.17%、从 3.69%下降至 2.88%),表明模型在真实业务场景中的识别稳定性与可靠性得到了进一步验证。
从长期想象空间看,DeepSeek-OCR2更像一次架构方向的试探:将文档的“阅读顺序与结构理解”能力前置至视觉编码器阶段,通过引入因果注意力机制实现视觉信息流的逻辑重排,使后端语言模型能够在更符合人类认知习惯的序列上进行推理。这一架构创新不仅为视觉-语言模型(VLM)的设计提供了新的技术路径,也使其能够作为生成高质量、强结构化训练数据的工具,从而反哺大语言模型的预训练与优化。此外,研发团队清晰界定了当前模型的适用边界,并明确了后续迭代方向(例如针对文本密集的报纸类文档,计划通过局部裁剪优化与专项数据补充进行改善)。这种“问题可归因、优化有路径”的迭代方法论,有助于形成持续、稳定的产品化演进能力,为模型的长期应用与商业化落地奠定了坚实基础。
风险:1)竞争加剧2)供应链风险3)算力成本与商业化变现不及预期风险
Fig.1 DeepEncoder vs DeepEncoder V2:从“扫描顺序”到“因果阅读顺序”

Source: DeepSeek, HTI
Fig.2 DeepEncoder vs DeepEncoder V2:从“扫描顺序”到“因果阅读顺序”

Source: DeepSeek, HTI

Fig.3 DeepSeek-OCR2端到端架构总览:DeepEncoder V2 + DeepSeek-3B解码器

Fig.4 DeepSeek-OCR 2 端到端架构总览:DeepEncoder V2 + DeepSeek-3B 解码器
Table 2 | Edit Distances for different categories of document-elements in OmniDocBench v1.5. $ V $ -token $ ^{max} $ denotes the lowest maximum number of visual tokens.
Model
V-tokenmax
TextEdit
FormulaEdit
TableEdit
R-orderEdit
OverallEdit
Gemini-3 pro[44]
1120
-
-
-
-
0.115
Seed-1.8[41]
5120
-
-
-
-
0.106
DeepSeek-OCR
1156
0.073
0.236
0.123
0.085
0.129
DeepSeek-OCR2
1120
0.048
0.198
0.096
0.057
0.100
Source: DeepSeek, HTI

Appendix
English Summary
Event
On January 27, 2026, the DeepSeek team officially released its research paper DeepSeek-OCR 2: Visual Causal Flow and simultaneously open-sourced a dedicated model for OCR and document parsing, DeepSeek-OCR 2 (hereafter "DeepSeek-OCR2"). The core upgrade of the new version lies in a breakthrough improvement to its visual encoder, DeepEncoder V2. This design enables the model to move beyond the traditional "top-to-bottom, left-to-right" mechanical scanning paradigm and instead perform dynamic understanding based on document layout features and semantic relationships. As a result, it achieves more human-like capabilities in parsing text, tables, and formulas, with the potential to significantly improve the accuracy and efficiency of complex document processing.
Commentary
This upgrade targets one of the hardest problems in document understanding: determining the correct reading order for complex layouts. When processing complex documents—such as multi-column pages, nested tables, and formula-rich text—traditional OCR systems and most vision-language models often treat "spatial order" as equivalent to "semantic order," leading to issues like concatenation errors and misalignment. DeepSeek-OCR 2 addresses this bottleneck with two key changes: it replaces the original CLIP-style encoder with a lightweight language model, Qwen2-500M, and introduces a "causal flow query" mechanism with causal attention. This allows the model to reorganize visual tokens by content logic during encoding, effectively "straightening out" the structure before decoding. In practice, it mirrors a human cognitive process: first grasp the global layout, then read content in a coherent order-materially improving semantic continuity and recognition accuracy on complex pages.
Public benchmarks suggest the model has entered the top tier. On the widely used document understanding benchmark OmniDocBench v1.5, DeepSeek-OCR 2 achieves an overall score of 91.09% representing a 3.73 percentage-point improvement over the previous generation. Its edit-distance metric reflecting reading-order quality improves from 0.085 to 0.057, validating the effectiveness of its "structure-first reading" approach in enhancing coherence. In peer comparison, while it is still slightly below the top-ranked PaddleOCR-VL (92.86%) the gap has narrowed to a small margin, indicating performance approaching industryleading levels. Particularly notable is efficiency: under the same visual token budget (1120), DeepSeek-OCR 2 records a documentparsing edit distance of 0.100, outperforming Gemini 3 Pro at 0.115 (lower is better). This demonstrates an excellent performance efficiency balance: high compression without sacrificing quality.
The implications for real-world deployment are straightforward: lower cost and stronger document parsing. From an efficiency standpoint, the model processes complex pages using only 256 to 1120 visual tokens. This high information compression can significantly reduce compute load and latency when downstream LLMs handle PDFs, scanned documents, financial statements, research reports, and contracts. The model is open-sourced under the Apache-2.0 license and comes with 3B parameters—an accessible scale and permissive licensing that make it easier to integrate into enterprise workflows. Potential use cases include PDF-to-Markdown conversion, structured extraction of tables and formulas, and RAG knowledge-base construction. Production feedback also appears encouraging: in real-world online log images and batch PDF processing tasks, the text "duplication rate" improves meaningfully (e.g., from 6.25% to 4.17% , and from 3.69% to 2.88%) , suggesting improved stability and reliability in practical settings.
Looking further ahead, DeepSeek-OCR 2 can be viewed as an architectural exploration: it pushes "reading order and structural understanding" upstream into the visual encoder. By using causal attention to reorder the visual information flow logically, it enables the backend language model to reason over sequences that better match human reading habits. This innovation not only offers a new design path for vision-language models (VLMs) but also positions the model as a practical tool for generating highquality, highly structured training data—potentially benefiting broader LLM pretraining and optimization. Moreover, the team clearly defines current limitations and outlines iterative directions—for example, improving performance on text-dense newspaper-like documents via local cropping strategies and targeted data augmentation. This "root-cause identifiable, optimization path clear" iteration methodology supports sustained productization and lays a solid foundation for long-term application and commercialization.
Risks: 1) Intensifying competition; 2) Supply chain risks; 3) Risk that compute costs and monetization fall short of expectations

附录APPENDIX
重要信息披露
本研究报告由海通国际分销,海通国际是由海通国际研究有限公司(HTIRL),Haitong Securities India Private Limited(HSIPL),Haitong International Japan K.K.(HTIJKK)和海通国际证券有限公司(HTISCL)的证券研究团队所组成的全球品牌,海通国际证券集团(HTISG)各成员分别在其许可的司法管辖区内从事证券活动。
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HTIRL 分析师认证 Analyst Certification:
我,姚书桥,在此保证(i)本研究报告中的意见准确反映了我们对本研究中提及的任何或所有目标公司或上市公司的个人观点,并且(ii)我的报酬中没有任何部分与本研究报告中表达的具体建议或观点直接或间接相关;及就此报告中所讨论目标公司的证券,我们(包括我们的家属)在其中均不持有任何财务利益。我和我的家属(我已经告知他们)将不会在本研究报告发布后的30个自然日内交易此研究报告所讨论目标公司的证券。I, Barney Yao, certify that (i) the views expressed in this research report accurately reflect my personal views about any or all of the subject companies or issuers referred to in this research and (ii) no part of my compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this research report; and that I (including members of my household) have no financial interest in the security or securities of the subject companies discussed. I and my household, whom I have already notified of this, will not deal in or trade any securities in respect of the issuer that I review within 30 calendar days after the research report is published.
我,吕小潼,在此保证(i)本研究报告中的意见准确反映了我们对本研究中提及的任何或所有目标公司或上市公司的个人观点,并且(ii)我的报酬中没有任何部分与本研究报告中表达的具体建议或观点直接或间接相关;及就此报告中所讨论目标公司的证券,我们(包括我们的家属)在其中均不持有任何财务利益。我和我的家属(我已经告知他们)将不会在本研究报告发布后的30个自然日内交易此研究报告所讨论目标公司的证券。I, Xiaotong Lyu, certify that (i) the views expressed in this research report accurately reflect my personal views about any or all of the subject companies or issuers referred to in this research and (ii) no part of my compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this research report; and that I (including members of my household) have no financial interest in the security or securities of the subject companies discussed. I and my household, whom I have already notified of this, will not deal in or trade any securities in respect of the issuer that I review within 30 calendar days after the research report is published.
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优于大市
中性(持有)
弱于大市
优于大市
中性(持有)
弱于大市
海通国际股票研究覆盖率
93.9%
6.0%
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92.3%
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3.3%
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卖出,未来12-18个月内预期相对基准指数跌幅在 以上,基准定义如下
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as of December 31,2025
as of September 30,2025
Outperform
Neutral(hold)
Underperform
Outperform
Neutral(hold)
Underperform
HTI Equity Research Coverage
93.9%
6.0%
0.1%
92.3%
7.5%
0.2%
IB clients*
3.0%
4.0%
0.0%
3.3%
3.9%
0.0%
*Percentage of investment banking clients in each rating category.
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非印度证券的研究报告:本报告由海通国际证券集团有限公司(“HTISGL”)的全资附属公司海通国际研究有限公司(“HTIRL”)发行,该公司是根据香港证券及期货条例(第571章)持有第4类受规管活动(就证券提供意见)的持牌法团。该研究报告在HTISGL的全资附属公司Haitong International (Japan) K.K.(“HTIJKK”)的协助下发行,HTIJKK是由日本关东财务局监管为投资顾问。
印度证券的研究报告:本报告由从事证券交易、投资银行及证券分析及受 Securities and Exchange Board of India(“SEBI”)监管的 Haitong Securities India Private Limited(“HTSIPL”)所发行,包括制作及发布涵盖 BSE Limited(“BSE”)和 National Stock Exchange of India Limited(“NSE”)上市公司(统称为「印度交易所」)的研究报告。HTSIPL于2016年12月22日被收购并成为海通国际证券集团有限公司(“HTISG”)的一部分。
所有研究报告均以海通国际为名作为全球品牌,经许可由海通国际证券股份有限公司及/或海通国际证券集团的其他成员在其司法管辖区发布。
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非美国分析师披露信息:本项研究首页上列明的海通国际分析师并未在FINRA进行注册或者取得相应的资格,并且不受美国FINRA有关与本项研究目标公司进行沟通、公开露面和自营证券交易的第2241条规则之限制。
IMPORTANT DISCLAIMER
For research reports on non-Indian securities: The research report is issued by Haitong International Research Limited ("HTIRL"), a wholly owned subsidiary of Haitong International Securities Group Limited ("HTISGL") and a licensed corporation to carry on Type 4 regulated activity (advising on securities) for the purpose of the Securities and Futures Ordinance (Cap. 571) of Hong Kong, with the assistance of Haitong International (Japan) K.K. ("HTIJKK"), a wholly owned subsidiary of HTISGL and which is regulated as an Investment Adviser by the Kanto Finance Bureau of Japan.
For research reports on Indian securities: The research report is issued by Haitong Securities India Private Limited ("HSIPL"), an Indian company and a Securities and Exchange Board of India ("SEBI") registered Stock Broker, Merchant Banker and Research Analyst that, inter alia, produces and distributes research reports covering listed entities on the BSE Limited ("BSE") and the National Stock Exchange of India Limited ("NSE") (collectively referred to as "Indian Exchanges"). HSIPL was acquired and became part of the Haitong International Securities Group of Companies ("HTISG") on 22 December 2016.
All the research reports are globally branded under the name Haitong International and approved for distribution by Haitong International Securities Company Limited ("HTISCL") and/or any other members within HTISG in their respective jurisdictions.
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除非下文另有规定,否则任何希望讨论本报告或者就本项研究中讨论的任何证券进行任何交易的收件人均应联系其所在国家或地区的海通国际销售人员。
香港投资者的通知事项:海通国际证券股份有限公司(“HTISCL”)负责分发该研究报告,HTISCL是在香港有权实施第1类受规管活动(从事证券交易)的持牌公司。该研究报告并不构成《证券及期货条例》(香港法例第571章)(以下简称“SFO”)所界定的要约邀请,证券要约或公众要约。本研究报告仅提供给SFO所界定的“专业投资者”。本研究报告未经过证券及期货事务监察委员会的审查。您不应仅根据本研究报告中所载的信息做出投资决定。本研究报告的收件人就研究报告中产生或与之相关的任何事宜请联系HTISCL销售人员。
美国投资者的通知事项:本研究报告由HTIRL,HSIPL或HTIJKK编写。HTIRL,HSIPL,HTIJKK以及任何非HTISG美国联营公司,均未在美国注册,因此不受美国关于研究报告编制和研究分析人员独立性规定的约束。本研究报告提供给依照1934年“美国证券交易法”第15a-6条规定的豁免注册的「美国主要机构投资者」(“Major U.S. Institutional Investor”)和「机构投资者」(“U.S. Institutional Investors”)。在向美国机构投资者分发研究报告时,Haitong International Securities (USA) Inc.(“HTI USA”)将对报告的内容负责。任何收到本研究报告的美国投资者,希望根据本研究报告提供的信息进行任何证券或相关金融工具买卖的交易,只能通过HTI USA。HTI USA位于130 West 42nd Street,FL18,New York,NY10036 USA,电话+1212-351-6052。HTI USA是在美国于U.S. Securities and Exchange Commission(“SEC”)注册的经纪商,也是Financial Industry Regulatory Authority,Inc.(“FINRA”)的成员。HTIUSA不负责编写本研究报告,也不负责其中包含的分析。在任何情况下,收到本研究报告的任何美国投资者,不得直接与分析师直接联系,也不得通过HSIPL,HTIRL或HTIJKK直接进行买卖证券或相关金融工具的交易。本研究报告中出现的HSIPL,HTIRL或HTIJKK分析师没有注册或具备FINRA的研究分析师资格,因此可能不受FINRA第2241条规定的与目标公司的交流,公开露面和分析师账户持有的交易证券等限制。投资本研究报告中讨论的任何非美国证券或相关金融工具(包括ADR)可能存在一定风险。非美国发行的证券可能没有注册,或不受美国法规的约束。有关非美国证券或相关金融工具的信息可能有限制。外国公司可能不受审计和汇报的标准以及与美国境内生效相符的监管要求。本研究报告中以美元以外的其他货币计价的任何证券或相关金融工具的投资或收益的价值受汇率波动的影响,可能对该等证券或相关金融工具的价值或收入产生正面或负面影响。美国收件人的所有问询请联系:
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130 West 42nd Street, FL 18
New York, NY 10036
联系人电话:+1212-351-6052
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Notice to Hong Kong investors: The research report is distributed by Haitong International Securities Company Limited ("HTISCL"), which is a licensed corporation to carry on Type 1 regulated activity (dealing in securities) in Hong Kong. This research report does not constitute a solicitation or an offer of securities or an invitation to the public within the meaning of the SFO. This research report is only to be circulated to "Professional Investors" as defined in the SFO. This research report has not been reviewed by the Securities and Futures Commission. You should not make investment decisions solely on the basis of the information contained in this research report. Recipients of this research report are to contact HTISCL salespersons in respect of any matters arising from, or in connection with, the research report.
Notice to U.S. investors: As described above, this research report was prepared by HTIRL, HSIPL or HTIJKK. Neither HTIRL, HSIPL, HTIJKK, nor any of the non U.S. HTISG affiliates is registered in the United States and, therefore, is not subject to U.S. rules regarding the preparation of research reports and the independence of research analysts. This research report is provided for distribution to "major U.S. institutional investors" and "U.S. institutional investors" in reliance on the exemption from registration provided by Rule 15a-6 of the U.S. Securities Exchange Act of 1934, as amended. When distributing research reports to "U.S. institutional investors," HTI USA will accept the responsibilities for the content of the reports. Any U.S. recipient of this research report wishing to effect any transaction to buy or sell securities or related financial instruments based on the information provided in this research report should do so only through Haitong International Securities (USA) Inc. ("HTI USA"), located at 130 West 42nd Street, FL 18, New York, NY 10036 USA; telephone +1 212-351-6052. HTI USA is a broker-dealer registered in the U.S. with the U.S. Securities and Exchange Commission (the "SEC") and a member of the Financial Industry Regulatory Authority, Inc. ("FINRA"). HTI USA is not responsible for the preparation of this research report nor for the analysis contained therein. Under no circumstances should any U.S. recipient of this research report contact the analyst directly or effect any transaction to buy or sell securities or related financial instruments directly through HSIPL, HTIRL or HTIJKK. The HSIPL, HTIRL or HTIJKK analyst(s) whose name appears in this research report is not registered or qualified as a research analyst with FINRA and, therefore, may not be subject to FINRA Rule 2241 restrictions on communications with a subject company, public appearances and trading securities held by a research analyst account. Investing

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中华人民共和国的通知事项:在中华人民共和国(下称“中国”,就本报告目的而言,不包括香港特别行政区、澳门特别行政区和台湾)只有根据适用的中国法律法规而收到该材料的人员方可使用该材料。并且根据相关法律法规,该材料中的信息并不构成“在中国从事生产、经营活动”。本文件在中国并不构成相关证券的公共发售或认购。无论根据法律规定或其他任何规定,在取得中国政府所有的批准或许可之前,任何法人或自然人均不得直接或间接地购买本材料中的任何证券或任何实益权益。接收本文件的人员须遵守上述限制性规定。
加拿大投资者的通知事项:在任何情况下该等材料均不得被解释为在任何加拿大的司法管辖区内出售证券的要约或认购证券的要约邀请。本材料中所述证券在加拿大的任何要约或出售行为均只能在豁免向有关加拿大证券监管机构提交招股说明书的前提下由Haitong International Securities (USA) Inc.(“HTI USA”)予以实施,该公司是一家根据National Instrument 31-103 Registration Requirements, Exemptions and Ongoing Registrant Obligations(“NI 31-103”)的规定得到「国际交易商豁免」(“International Dealer Exemption”)的交易商,位于艾伯塔省、不列颠哥伦比亚省、安大略省和魁北克省。在加拿大,该等材料在任何情况下均不得被解释为任何证券的招股说明书、发行备忘录、广告或公开发行。加拿大的任何证券委员会或类似的监管机构均未审查或以任何方式批准该等材料、其中所载的信息或所述证券的优点,任何与此相反的声明即属违法。在收到该等材料时,每个加拿大的收件人均将被视为属于 National Instrument 45-106 Prospectus Exemptions 第1.1节或者 Securities Act (Ontario)第73.3(1)节所规定的「认可投资者」(“Accredited Investor”),或者在适用情况下 National Instrument 31-103第1.1节所规定的「许可投资者」(“Permitted Investor”)。
新加坡投资者的通知事项:本研究报告由Haitong International Securities (Singapore) Pte Ltd(“HTISSPL”)于新加坡提供。HTISSPL是符合《财务顾问法》2001(“FAA”)定义的豁免财务顾问,可(a)提供关于证券,集体投资计划的部分,交易所衍生品合约和场外衍生品合约的建议(b)发行或公布有关证券、交易所衍生品合约和场外衍生品合约的研究分析或研究报告。本研究报告仅提供给符合《证券及期货法》2001第4A条项下规定的机构投资者。对于因本研究报告而产生的或与之相关的任何问题,本研究报告的收件人应通过以下信息与 HTISSPL联系:
Haitong International Securities (Singapore) Pte. Ltd
10 Collyer Quay, #19-01 - #19-05 Ocean Financial Centre, Singapore 049315
电话:(65)67130473
日本投资者的通知事项:本研究报告由海通国际证券有限公司所发布,旨在分发给从事投资管理的金融服务提供商或注册金融机构(根据日本金融机构和交易法(“FIEL”))第61(1)条,第17-11(1)条的执行及相关条款)。
英国及欧盟投资者的通知事项:本报告由从事投资顾问的Haitong International Securities Company Limited所发布,本报告只面向有投资相关经验的专业客户发布。任何投资或与本报告相关的投资行为只面对此类专业客户。没有投资经验或相关投资经验的客户不得依赖本报告。Haitong International Securities Company Limited的分支机构的净长期或短期金融权益可能超过本研究报告中提及的实体已发行股本总额的 0.5%。特别提醒有些英文报告有可能此前已经通过中文或其它语言完成发布。
澳大利亚投资者的通知事项:Haitong International Securities (Singapore) Pte Ltd, Haitong International Securities Company Limited 和 Haitong International Securities (UK) Limited分别根据澳大利亚证券和投资委员会(以下简称“ASIC”)公司(废除及过度性)文书第2016/396号规章在澳大利亚分发本项研究,该等规章免除了根据2001年《公司法》在澳大利亚为批发客户提供金融服务时海通国际需持有澳大利亚金融服务许可的要求。ASIC的规章副本可在以下网站获取:www.legislation.gov.au。海通国际提供的金融服务受外国法律法规规定的管制,该等法律与在澳大利亚所适用的法律存在差异。
印度投资者的通知事项:本报告由从事证券交易、投资银行及证券分析及受 Securities and Exchange Board of India(“SEBI”)监管的 Haitong Securities India Private Limited(“HTSIPL”)所发布,包括制作及发布涵盖 BSE Limited(“BSE”)和 National Stock Exchange of India Limited(“NSE”)(统称为「印度交易所」)研究报告。
(条款链接:https://www.htisec.com/sites/all/themes/hitong/files/india/Terms%20and%20Conditions%20for%20Research%20Analyst.pdf)
研究机构名称:Haitong Securities India Private Limited
SEBI 研究分析师注册号:INH000002590
地址:1203A,Floor 12A,Tower 2A,One World Center
841 Senapati Bapat Marg, Elphinstone Road, Mumbai 400 013, India
CIN U74140MH2011FTC224070
电话:+912243156800传真:+912224216327
合规和申诉办公室联系人:Prasanna Chandwaskar;电话:+912243156803;电子邮箱:prasanna.chandwaskar@htisec.com
“请注意,SEBI授予的注册和NISM的认证并不保证中介的表现或为投资者提供任何回报保证”。
版权所有:海通国际证券集团有限公司2019年。保留所有权利。

People's Republic of China (PRC): In the PRC, the research report is directed for the sole use of those who receive the research report in accordance with the applicable PRC laws and regulations. Further, the information on the research report does not constitute "production and business activities in the PRC" under relevant PRC laws. This research report does not constitute a public offer of the security, whether by sale or subscription, in the PRC. Further, no legal or natural persons of the PRC may directly or indirectly purchase any of the security or any beneficial interest therein without obtaining all prior PRC government approvals or licenses that are required, whether statutorily or otherwise. Persons who come into possession of this research are required to observe these restrictions.
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"Please note that Registration granted by SEBI and Certification from NISM in no way guarantee performance of the intermediary or provide any assurance of returns to investors".
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