- ISBN:9787302564751
- 装帧:一般胶版纸
- 册数:暂无
- 重量:暂无
- 开本:16开
- 页数:244
- 出版时间:2021-02-01
- 条形码:9787302564751 ; 978-7-302-56475-1
本书特色
深入剖析智能投顾的前世今生、概念理论、商业模式、技术手段、实践案例、政策监管,助力从业者和研究人员精准把握智能投顾发展方向与本质。
内容简介
本书围绕智能投顾的前世与今生、概念与理论、商业模式与技术、智能投顾的监管、生态以及未来发展趋势进行归纳与分析。全书共9章。第1章阐释智能投顾的诞生,涉及金融科技概念、人工智能概念等;第2章介绍智能投顾涉及的技术、覆盖范围等;第3章阐释智能投顾的概念及投资流程;第4~6章从微观角度介绍智能投顾的商业模式与技术支持,涉及智能投顾的服务对象、投资标的、推广,传统经济学、统计学、行为学背景下智能投顾中的投资理论,以及人工智能和金融科技背景下智能投顾的前沿金融智能技术;第7章和第8章从宏观角度介绍智能投顾的政策支持与生态系统;第9章对智能投顾做出总结和展望。 本书内容丰富,观点超然,案例典型,结构清晰,适合对智能投顾感兴趣的从业者、研究人员、爱好者阅读。
目录
目录
第1章 智能投顾的诞生
案例:Betterment的诞生 ·················2
1.1 金融科技的兴盛 ·····················3
1.1.1 金融科技的概念 ················4
1.1.2 金融科技的全球发展态势 ·····5
1.1.3 金融科技在中国 ················9
1.2 人工智能的崛起 ···················13
1.2.1 人工智能的概念 ···············14
1.2.2 人工智能的全球发展态势 ····14
1.2.3 人工智能在中国 ···············18
1.2.4 人工智能投融资状况 ··········19
1.3 智能投顾应运而生 ················20
1.4 本书概览····························21
本章小结 ··································22
参考文献 ··································22
第2章 智能投顾的历史与发展现状
案例:中美智能投顾发展比较 ········25
2.1 智能投顾的发展历史 ·············27
2.1.1 标签过滤阶段 ··················29
2.1.2 用户风险承受能力测试阶段···29
2.1.3 个性化投资组合推荐阶段 ····30
2.1.4 全自动智能投顾阶段 ··········31
2.2 智能投顾产业全球的发展现状 ··31
2.2.1 全球智能投顾发展数据总览···31
2.2.2 美洲 ······························33
2.2.3 欧洲 ······························37
2.2.4 亚洲 ······························39
2.3 智能投顾在中国 ···················40
2.3.1 中国的智能投顾平台现状 ····40
2.3.2 中国智能投顾行业发展现状···42
2.3.3 中国智能投顾的发展机遇 ····47
本章小结 ··································49
参考文献 ··································50
第3章 智能投顾的概念与投资流程
案例:Betterment的投资流程 ·········53
3.1 智能投顾的概念 ···················54
3.1.1 传统的投资顾问 ···············54
3.1.2 智能投资顾问 ··················55
3.1.3 智能投顾的作用 ···············58
3.2 智能投顾的投资流程 ·············60
3.2.1 客户分析 ························61
3.2.2 大类资产配置 ··················63
3.2.3 投资组合选择 ··················65
3.2.4 交易执行 ························66
3.2.5 投资组合再选择 ···············67
3.2.6 税负管理 ························69
3.2.7 组合分析 ························70
本章小结 ··································70
参考文献 ··································71
第4章 智能投顾的商业模式
案例:Betterment的商业模式 ·········73
4.1 智能投顾的目标客户 ·············74
4.1.1 中产及中产以下收入人群 ····75
4.1.2 金融专业人士 ··················77
4.2 智能投顾的投资标的 ·············78
4.2.1 常见的投资标的 ···············78
4.2.2 新兴的投资标的 ···············81
4.3 智能投顾的业务模式 ·············82
4.3.1 全自动与半自动投顾 ··········83
4.3.2 投资平台与相关智能服务 ····87
4.3.3 大类资产配置、投资策略与社交跟投等 ··················88
4.4 智能投顾的营销模式 ·············89
4.4.1 打造明星产品 ··················90
4.4.2 分级客户群匹配服务,提高服务水平 ··················91
4.4.3 利用大数据进行精准营销 ····91
4.5 智能投顾的盈利模式 ·············92
4.5.1 前端收费模式 ··················93
4.5.2 后端盈利模式 ··················94
本章小结 ··································94
参考文献 ··································95
第5章 智能投顾理论入门
案例:马科维茨理论的产生 ···········98
5.1 马科维茨投资组合理论 ··········99
5.1.1 现代投资组合理论概述 ·······99
5.1.2 投资组合的可行集和有效集 ·························100
5.1.3 均值方差分析方法···········101
5.2 资本资产定价模型 ···············102
5.2.1 CAPM假设条件 ·············103
5.2.2 分离定理 ······················104
5.2.3 资本市场线与证券市场线 ··106
5.3 套利定价理论 ·····················107
5.3.1 APT概述······················107
5.3.2 因素模型 ······················108
5.3.3 套利定价理论 ················110
5.4 行为金融学 ························111
5.4.1 行为金融学的概念···········112
5.4.2 行为金融学的应用实例 ·····114
5.5 投资过程评价 ·····················115
5.5.1 收益类指标 ···················115
5.5.2 风险类指标 ···················116
本章小结 ·································118
参考文献 ·································118
第6章 智能投顾中的人工智能技术
案例:嘉信智能理财 ···················121
6.1 大数据融合技术 ··················121
6.1.1 大数据融合的背景···········122
6.1.2 多源数据融合技术···········123
6.2 投资客户偏好画像 ···············125
6.2.1 用户画像的定义 ·············126
6.2.2 用户画像的生成流程 ········128
6.2.3 客户画像的核心工作——打标签 ·························129
6.3 量化投资技术 ·····················130
6.3.1 量化投资的概念 ·············130
6.3.2 机器学习应用到量化投资中 ·························131
6.3.3 深度学习应用到量化投资中 ·························135
6.4 投资组合配置技术 ···············138
6.4.1 问题定义 ······················138
6.4.2 二次规划 ······················140
6.4.3 强化学习 ······················142
6.5 投资风险控制技术 ···············144
6.5.1 风险的定义 ···················145
6.5.2 风险测量—方差···········145
6.5.3 风险测量—VaR ···········146
6.6 NLP在智能金融领域中的应用 ································147
6.6.1 智能金融领域现有需求 ·····148
6.6.2 NLP的金融应用场景 ·······149
6.6.3 NLP在金融领域应用案例 ····························153
本章小结 ·································155
参考文献 ·································156
第7章 智能投顾的风险、监管和政策支持
案例:真假智能投顾 ···················160
7.1 中国智能投顾的风险 ············161
7.1.1 智能投顾的风险构成 ········161
7.1.2 智能投顾的风险预警 ········163
7.1.3 智能投顾平台的风险指数体系 ······················164
7.2 智能投顾的监管难点 ············167
7.2.1 账户实际控制人认定困难 ··168
7.2.2 一致行动人 ···················168
7.2.3 监管法律体系不完善 ········168
7.2.4 智能投顾行为边界判定 ·····169
7.3 海外智能投顾的监管经验 ······170
7.3.1 美国的智能投顾监管 ········170
7.3.2 英国的智能投顾监管:监管沙盒 ······················171
7.3.3 澳洲的智能投顾监管 ········177
7.3.4 新加坡的智能投顾监管 ·····180
7.3.5 不同国家智能投顾的监管体系比较 ······················183
7.4 中国智能投顾的监管体系 ······185
7.4.1 智能投顾监管框架···········185
7.4.2 智能投顾的监管路径 ········187
7.5 中国智能投顾的政府支持 ······192
7.5.1 智能投顾发展过程中的政府政策 ······················192
7.5.2 《资管新规》对智能投顾的影响 ···················193
7.5.3 学界对智能投顾的支持 ·····195
本章小结 ·································196
参考文献 ·································196
第8章 智能投顾的生态系统
案例:新加坡的金融科技生态系统 ···199
8.1 金融科技生态系统 ···············200
8.2 智能投顾生态系统的概念与构成 ································203
8.2.1 智能投顾生态系统的概念 ··203
8.2.2 智能投顾生态系统的生态主体 ······················206
8.2.3 智能投顾生态系统中的产业链关系 ···················213
8.3 智能投顾生态系统的维护和优化 ································217
8.3.1 国内智能投顾生态系统存在的缺陷 ···················217
8.3.2 智能投顾生态系统的优化办法 ······················218
本章小结 ·································220
参考文献 ·································220
第9章 智能投顾的未来
案例:蚂蚁集团—从FinTech到TechFin,BASIC科技战略打造折叠式生态体系 ························223
9.1 人工智能的发展新阶段 ·········223
9.2 智能投顾大脑 ·····················225
9.3 AI驱动的理性机器经济人 ······227
9.4 智能投顾的未来发展趋势 ······229
9.4.1 商业模式发展趋势···········229
9.4.2 智能投顾技术发展趋势 ·····230
9.4.3 智能投顾监管发展趋势 ·····231
9.5 开放银行与虚拟银行 ············232
9.5.1 开放银行 ······················232
9.5.2 虚拟银行 ······················233
本章小结 ·································234
参考文献 ·································234
作者简介
郑小林,博士,浙江大学计算机学院教授,人工智能研究所副所长,斯坦福大学访问学者,阿里巴巴青年学者理事会理事,入选浙江省151人才工程,担任杭州金智塔科技有限公司首席科学家。主持国家、省部级项目和课题10多项;以**或通讯作者发表学术论文50多篇;作为主要骨干获得2020年“CCF科学技术奖”卓越奖(一等奖),2018年教育部科技进步奖二等奖,2014年浙江省科技进步奖一等奖;荣获2009年阿里巴巴青年学者计划优秀学者,2009 IBM中国优秀教师奖教金。 贲圣林,博士,先后获得清华大学工程学士学位、中国人民大学企业管理硕士学位和美国普渡大学经济学博士学位。现任浙江大学国际联合商学院院长、互联网金融研究院院长、管理学院教授。兼任中国人民大学国际货币研究所联席所长,全国工商联国际委员会委员,中华海外联谊会常务理事,中央统战部党外知识分子建言献策专家组成员,浙江省政协常委、经济委员会副主任,浙江省人民政府参事,浙江互联网金融联合会联合主席,广东金融专家顾问委员会顾问委员等。
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