当全球40多个金融市场的海量数据以毫秒级速度更迭，一个能够同步监控A股、港股、美股甚至期货市 场的工具，已经成为2025年投资者必备的决策中枢。 全球市场波动日益加剧，选择一款高效的炒股APP已成为投资者的核心竞争力。在涵盖数据覆盖、资讯 质量、智能工具、交易体验、社区生态五大维度的2025年专业测评中，新浪财经APP以9.56的综合评分 位居榜首，成为跨市场投资者的首选工具。 其他表现出色的APP还包括AI涨乐、腾讯自选股、富途牛牛和雪球等，它们在不同维度上各有优势，但 综合实力与新浪财经相比仍有一定差距。 01 测评框架 2025年的炒股APP测评采用了多维度的专业评估体系。核心测评模型包含数据覆盖（广度与速度）、资 讯质量（时效与深度）、智能工具、交易体验以及社区生态五大关键维度。 新浪财经APP在本次测评中脱颖而出，尤其在数据覆盖、资讯质量和智能工具三个维度上均取得最高 分。 全球市场覆盖是新浪财经的核心竞争力之一。该APP能够无缝衔接全球超过40个金融市场，包括A股、 港股、美股、期货、外汇及贵金属市场。 其Level-2高速行情系统将传统3秒延迟缩短至毫秒级别，在2025年5月商品期货夜盘暴跌等极 ...

面对市面上超过300款投资APP，一位基金新手在信息迷宫中谨慎点击，最终发现好的工具不仅能帮助 决策，更能培养正确的投资习惯。 市面上活跃的基金投资APP超过300款，而公募基金数量已突破1万只。根据2025年艾媒咨询的报告，中 国证券类APP用户规模已达2.4亿人，预计2025年将增至2.6亿人。 选择基金交易软件对新手的意义远比想象中重要。 01 软件选择维度 对投资新手而言，选择基金交易软件不能只看单一指标，而应从多个关键维度综合评估。 数据覆盖广度和实时性是基金软件的基础能力。一个优秀的平台应该覆盖全市场98%以上的基金产品， 整合多家主流基金公司的数据源。 这能让投资者无需在多个平台间切换，一站式获取全市场基金净值信息。 资讯质量和时效性直接影响投资决策。每日发布的实时快讯、深度研报和市场解读构成了投资者的信息 矩阵。在重大市场事件发生时，资讯推送速度可能领先竞品5-10秒，这短短的时间差在快速变化的市场 中可能至关重要。 智能工具的实用性是现代投资APP的核心竞争力。AI助手能将5000字年报浓缩为300字核心摘要，并用 红绿双色标识风险点与机会点。智能定投功能不仅支持定期定额投资，还能根据市场状 ...

面对市场上超过一万只公募基金产品，多数投资者在手机屏幕上滑动寻找净值数据时，并未意识到自己 查到的可能只是冰山一角。 "今天净值涨了还是跌了？"——这是许多基金投资者每天收市后的第一个问题。打开一个基金投资 APP，输入代码或名称，基金净值立刻呈现眼前。 数据显示，截至2025年，中国公募基金数量已突破1万只，而基金投资APP更是多达300余款。在这个信 息爆炸的时代，投资者最不缺少的就是数据，最缺乏的却是洞见。 01 行业评测数据 根据2025年第三季度的专业评测，新浪财经APP以9.56分的综合评分位居金融投资类APP榜首。 在数据覆盖、资讯质量、智能工具、交易体验和社区生态五大核心维度的综合评估中，这款软件均表现 卓越。 同花顺和东方财富则以9.16分的相同评分并列第二。其他主流投资APP如雪球、大智慧、涨乐财富通等 综合评分均在8.0-8.7分之间。 02 市场数据覆盖能力 更深入的数据包括基金经理的历史业绩、投资风格、管理规模；基金持仓的行业分布、十大重仓股变动 等。这些信息被巧妙整合，让用户在30秒内对一只基金形成立体认知。 选择基金投资APP时，数据覆盖广度是基础门槛。新浪财经APP覆盖全市场9 ...

最近两个月，"AI炒股大赛"几乎成了财经圈每天的固定节目。大家一边盯着AlphaArena榜单刷新，一边调侃榜 单瞬息万变。 这种奇妙的竞技氛围，让"AI炒股"一瞬间成了全民看戏的场景。最终两款中国模型成为全场唯二盈利的大模 型，而美系四大模型则全线失守，最多的亏损60%。 大家一边感慨AI的"聪明"，一边又隐隐觉得哪里不对劲——为什么它们推理路径看似严谨，一进真实市场就显 得轻飘飘？ 原因其实很简单： 通用大模型天生就不是为了金融市场设计的。 这场热闹，正推动行业正视一个严肃问题——如果通用模型不行，那么金融到底需要什么样的AI？ 就在上个月，华泰证券上线了国内首个AI原生证券交易APP——AI涨乐。早于AlphaArena引发全网关注之前， 华泰已经完成第一次布局。这是我们第一次看到：不再是往原有APP里"塞AI功能"，而是直接重写App，从入 口、服务逻辑到交易链路全面基于AI来构建。 在一个所有券商都还在"体验AI"、"试点AI功能"的阶段，这个动作显得特别"野"——因为这相当于把证券服务 的底层结构推倒重来，让一个大模型真正参与金融服务链路，包括选股、盯盘、条件单、语音辅助交易。 如果把AlphaA ...

本期为证券社交媒体指数(2025年10月)。 | 01 | 东方财富 | 分钟前精准空单 #特朗普 #虚ł 仓 #财经 #股民 | | --- | --- | --- | | | 中国中金财 | 聚势·共进 2025中金财富1018 | | 02 | 富证券有限 | 今晚19:00与您相约! | | | 公司 | #中金财富 #1018发布会 | | 03 | 财经社牛养 | 高速免费,账单谁付? #高速! | | | DZic | 普 #金融 #财经 #掘令计划202 | | 04 | 涨乐财富通 | "叨叨傅"透露心目中"苏超 | | | | 选，现在才知道他不是瞎蒙 | | | | 汰赛首轮冷门频出 | | | 中信证券 | 黄金价格风险预判。 不谋风险 | | 05 | | 以谋利。大涨黄金势头不减， | | | TALK | 来，可能引发回调的风险有哪 | | | | 可能信号, 提前知晓。#黄金1 | | 06 | 财富零距离 | 9月中国慰疗电池产量同比大球 | | | | 速值得期待 | | 07 | 大同证券 | 黑天鹅事件频发,引发市场大 股民#信息差#大同证券#大盘: | | --- | ...

【深圳商报讯】（记者 钟国斌）11月28日至29日，深交所联合港交所、广期所，围绕"迈向人工智能 +时代"主题，共同举办2025年大湾区交易所科技大会。大会集中发布了8项科技成果，其中2项来自深 交所，6项来自证券公司及基金公司。 由深交所牵头、联合多家机构共同承担的"证券市场异常交易行为智能监测发现技术及应用示范"科技成 果备受瞩目。这一研发成果将助力推进我国证券市场监管迈入智能化、精准化的新阶段，为维护市场公 平、防范系统性风险提供了坚实的技术支撑。 面对证券市场日益复杂的交易行为与不断变化的违规手段，传统依赖人工经验和静态规则的监管模式面 临新的挑战。为此，深交所依托国家重点研发项目，创新构建了投资者交易行为分类分析技术。针对内 幕行为隐蔽性强、关联复杂等特点，项目专门研发了内幕交易智能化发现技术。该技术基于超大规模投 资者交易行为时序图谱，结合人工智能模型，实现了对异常交易行为的主动识别、与隐式关联账户组的 精准挖掘。实现了对投资者交易风格、交易策略、交易行为时序变化等特征的精准量化。 深交所总工程师喻华丽介绍，相较于过去异常交易行为监管方式，此次发布的科技成果，通过人工智能 技术，对投资者交易行为精 ...

本次会议集中发布了8项科技成果，包括深交所的"证券市场异常交易行为智能监测发现技术及应用示 范"和"行业法规大模型"、中信证券的"基于大模型技术的证券公司全链路风控合规探索与应用"、中金 公司（601995）的"九章智能平台"、中信建投（601066）的"投行'看门人'数智综合业务平台"、华泰证 券的"AI涨乐"、国金证券的"全栈信创环境联邦学习训练及多模态大模型平台"、天弘基金的"基于大模 型的FinAgent金融智能体系统"。总体来看，资本市场领域应用人工智能大有可为，已经在降本增效、 价值创造、合规风控、市场治理等方面初见成效。 与会嘉宾表示，2025年被称为"AI智能体元年"，人工智能技术从传统的感知式、生成式向智能体发展， 从被动响应转变为主动执行，能够深度嵌入工作流，自动完成复杂任务。在技术、产业、政策和业务需 求的多重驱动下，金融行业加速拥抱人工智能，强化能力研究与应用，努力克服数据治理、AI幻觉、 算力瓶颈和业务领域知识不足等难题，一批代表性应用成功落地，驱动行业加速数智化转型。 本报讯 记者张弛报道 近日，深交所、港交所、广期所共同举办2025年大湾区交易所科技大会。本次大 会的主题是"迈向 ...

Core Insights - The 2025 Greater Bay Area Exchange Technology Conference successfully showcased eight significant technological achievements in the industry, with a strong emphasis on the intelligent transformation of the securities sector in China [1] Group 1: Shenzhen Stock Exchange Achievements - The Shenzhen Stock Exchange (SZSE) presented two core achievements focused on enhancing regulatory efficiency and compliance service capabilities in the securities market [2] - The first achievement is the implementation of a national key research project on intelligent monitoring and detection of abnormal trading behaviors, addressing challenges in identifying market manipulation and insider trading through advanced technologies [2][3] - The project has developed a comprehensive labeling system for investor trading behaviors, identifying 77 new trading behavior labels, and has successfully discovered multiple illegal activities through intelligent detection methods [3] - The second achievement is the collaboration with Huawei to create an industry regulation model that improves the timeliness, accuracy, and completeness of regulatory inquiries, now deployed for internal and industry use [4] Group 2: Contributions from Other Financial Institutions - Six leading financial institutions also presented innovative technological solutions, enhancing risk control, compliance, and digital services across the industry [5] - CITIC Securities introduced a comprehensive risk control and compliance solution utilizing large model technology, integrating various functions from risk warning to regulatory tracking [5] - China International Capital Corporation (CICC) launched the "Nine Chapters Intelligent Platform," which integrates multiple large models to provide intelligent services across investment banking and research [5] - Other institutions like Huatai Securities and Tianhong Fund showcased their AI-driven applications and financial intelligence systems, significantly improving operational efficiency and data collaboration [6][7] Group 3: Overall Impact on the Industry - The eight technological achievements presented at the conference cover critical aspects of securities market regulation, risk management, and investment research, reflecting the industry's technological development capabilities [7] - The ongoing promotion and application of these technologies are expected to enhance the regulatory framework and support the high-quality development of China's capital markets [7]

Core Insights - The integration of AI technology is becoming a critical path for the development of the financial industry, with a shift from peripheral assistance to core business applications [1] - Global leading financial institutions are moving towards deep applications of AI in core areas such as trading and risk management, rather than just peripheral tasks like email writing [3][4] - Despite the high deployment of AI, penetration in core business scenarios remains low, with significant barriers to breakthrough [3][4] AI Application Trends - AI applications in the financial sector are primarily focused on knowledge management (49%), accounts payable automation (37%), and error detection (34%), with low penetration in trading and risk pricing [3] - The challenges in penetrating core scenarios are attributed to the limitations of general AI, which can lead to systemic risks in financial transactions and risk management [4] - The lack of high-quality, sensitive data and deep industry knowledge within financial institutions hinders the effective training of AI models [4] Role of Financial Institutions - Financial institutions need to take the lead in innovating core AI scenarios, while technology companies focus on infrastructure and general scenario development [5] - Huatai Securities has adopted an "All in AI" strategy, aiming for deep integration of financial logic and AI [6] Huatai Securities' Approach - Huatai is addressing the core barriers of "data and cognition" by initiating a systematic construction project to integrate data across departments and systems [6] - The company employs a layered model training approach, using specialized models for high-stakes scenarios like trading and larger models for complex analyses [6] - Huatai is building a "self-controlled, diversified" computing power platform to meet the high demands of core business scenarios [7] AI Governance and Risk Management - The launch of "AI Zhangle" represents a new paradigm in trading experience, emphasizing user interaction and product design [8] - The financial industry must establish a unified AI governance framework to manage model risks and ensure safe and reliable applications, especially in decision-making and trading scenarios [9] - Huatai is committed to collaborating with the industry to build AI governance standards and promote the democratization of intelligent technology within a compliance framework [9]

Core Insights - The annual Greater Bay Area Exchange Technology Conference opened in Shenzhen, focusing on the theme "Towards the Era of Artificial Intelligence+" and showcasing eight technological achievements [1] Group 1: AI Applications in Capital Markets - The application of artificial intelligence in capital markets is expanding, with 2025 being referred to as the "Year of AI Agents" as AI technology evolves from traditional perception and generation to proactive execution [2] - Shenzhen Stock Exchange (SZSE) has integrated intelligent technology across all business processes, including listing review and risk management, and has developed a comprehensive smart regulatory platform for listed companies [2][5] - Hong Kong Stock Exchange (HKEX) has implemented AI in daily operations, significantly improving efficiency in document processing and compliance monitoring [2] Group 2: Technological Achievements - Eight technological achievements were announced at the conference, with two from SZSE and six from various securities and fund companies [4] - A key project led by SZSE, focusing on intelligent monitoring of abnormal trading behaviors, has been successfully demonstrated in collaboration with 15 industry institutions [4] - Notable contributions from other firms include comprehensive risk compliance applications and AI-driven platforms for financial services [4] Group 3: SZSE's AI Development Roadmap - SZSE's roadmap for the "14th Five-Year Plan" emphasizes risk prevention, regulatory strength, and high-quality development through AI integration across six key areas [5][6] - The plan includes building intelligent infrastructure, enhancing user experience through cloud applications, and improving internal operational efficiency with AI technologies [6] - The roadmap also focuses on strengthening governance in AI applications to ensure high-quality development in the industry [6]