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Jingdong book

数量化股票投资:技术与策略

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数量化股票投资:技术与策略

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《数量化股票投资:技术与策略》讨论的是如何利用现代技术来进行数量化股票投资组合的管理。《数量化股票投资:技术与策略》的目标之一就是从理论和实践两个角度介绍数量化股票投资组合管理的发展,它们可以被称作“高级股票投资组合管理的最高水平”。我们的讨论覆盖了在当今行业中使用的数量化股票投资组合管理的最常用技术、工具和策略。对于很多高级的话题,我们为读者提供了在其领域中最新的应用性研究文献。
本书适用于学生、专业学者以及那些想要了解股票投资组合管理中最新的数量化技术和想要在这个迅速发展的领域中深化理解最前沿技术的金融从业人员。本书的写作相对独立,因此几乎不需要金融学的背景知识。不过,大学本科课程中线性代数和概率论的基本应用知识还是需要的,特别是对于本书中那些更偏重于数学的话题来说更是如此。
《数量化股票投资:技术与策略》的很多章节都可用于数量化投资管理、计量经济学、交易策略和算法交易的课程和实习中。《数量化股票投资:技术与策略》适合于大学本科投资管理的高级选修课和金融学、经济学或者是数学及物理学的研究生使用。
Content Description

《数量化股票投资:技术与策略》介绍了目前高缀股票投资缝合定量管理中最常见的技术、工具和策略,包括回归分析、主成分分析、时间序列分析、算法交易、贝叶斯组合最优化技术、鲁棒组合最优化等。在很多前沿领域,作者提供了该领域最新的有应用价值的研究成果。《数量化股票投资:技术与策略》的读者对象是想要了解股票投资组合定量管理领域最新进展的学生、学者和金融从业人员。
Author Description

弗兰克.J.法博兹,耶鲁大学管理学院金融实务方向的教授和卡尔斯鲁厄大学统计、计量与数理金融学院的合聘教授,耶鲁大学金融国际中心和美国普林斯顿大学运筹与金融工程系咨询委员会的成员。2007年获得了CFA协会授予的C.Stewart Sheppard奖。著有《金融学中的贝叶斯方法》(2008)、《金融计量学:从基础到高级的建模技术》(2007)等图书。

塞尔吉奥.M.福卡尔迪,尼斯高等商学院的金融学教授和总部设在巴黎的天祥集团咨询公司的创办合伙人,《投资组合管理》杂志编辑委员会的成员。
彼特.N.科姆,纽约大学柯朗数学科学研究所金融数学硕士项目的副主任和副教授以及总部位于纽约的Heimdall集团金融咨询有限责任公司的创办合伙人。
赵胜民,南开大学金融学系金融工程学教研室主任、金融工程专业博士生导师。天津大学系统工程研究所系统工程专业博士毕业。曾就职于天津大学管理学院金融工程研究中心。研究领域为金融工程、线性控制系统、生存理论。讲授“微分方程”、“随机过程”、“金融经济学”、“金融工程”等课程。
Catalogue

第一章 导论
数理金融礼赞
数量化股票管理的应用研究
为什么实施数量化过程?
进入壁垒
数量化股票投资的展望

第二章 金融计量经济学Ⅰ:线性回归
历史记载
协方差和相关系数
回归、线性回归和投影
多变量回归
分位数回归
回归诊断
回归的稳健性估计
分类回归树
总结

第三章 金融计量经济学Ⅱ:时间序列
随机过程
时间序列
稳定的向量自回归过程
单整变量和协整变量
稳定的向量自回归(VAR)模型的估计
滞后期的估计
残差的自相关性以及分布性质
平稳的自回归分布滞后模型
非平稳的VAR模型估计
利用典型相关方法估计
利用主成分分析法估计
利用伴随矩阵特征值估计
金融学中的非线性模型
因果关系
总结

第四章 金融建模中常见的错误
理论与工程
工程学与理论科学
工程学与金融产品设计
投资组合管理的学习方法、理论方法以及混合方法
样本偏差
平均值的偏差
从大型数据集中进行抽样的错误
模型的时间聚集性以及数据频率选择中的错误
模型风险及其规避方法
总结

第五章 因素模型及其估计
因素的概念
静态因素模型
因素分析与主成分分析
为什么使用收益的因素模型
收益的近似因素模型
动态因素模型
总结

第六章 基于因素的交易策略工:因素的构建和分析
基于因素的交易
构建基于因素的交易策略
交易策略的风险
因素的理想特性
因素的来源
基于公司特征的因素构建
数据处理
因素数据的分析
总结

第七章 基于因素的交易策略Ⅱ:横截面模型及交易策略
因素溢价评估的横截面方法
投资组合分类法
因素模型
因素表现的评估
基于因素的交易策略的模型构建方法
回溯测试
……
第八章 投资组合最优化:基本理论与实践
第九章 投资组合最优化:Bayes技术和Black-Litterman模型
第十章 鲁棒投资组合优化
第十一章 交易成本与交易执行
第十二章 投资管理与算法交易
索引

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Brand Jingdong book
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