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基于Python的金融分析与风险管理

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基于Python的金融分析与风险管理

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金融科技时代已经到来,善于将金融理论与IT技术进行深度融合的人,将成为新时代独具竞争力的金融科技类人才。无论是打算在金融领域求职的新人,还是希望进一步提升个人能力的“职场老手”,本书都值得一看。
1.内容前沿,将Python编程与金融分析、风险管理巧妙结合,引领金融科技新时代。
2.源于实践,完美整合了作者20余年的金融从业经验和Python编程实践。
3.实例丰富,提供244个金融实战案例,彰显Python在金融领域运用的简洁与高效。
4.注重效率,清晰的编程步骤和详尽的代码注释,帮你轻松理解并掌握Python编程。
5.覆盖面广,案例涵盖货币市场、债券市场、股票市场、期货市场和期权市场。
6.聚焦风控,深度剖析各类金融产品的风险,讨论风险管理的重要工具和量化模型。
Content Description

Python是一门开源的编程语言,凭借其易学和灵活的特点,得到了越来越多人的认可和青睐。它在金融领域也有着非常好的应用现状和前景。
本书聚焦于Python在金融分析与风险管理的应用,全书分为入门篇、基础篇和提高篇,共12章。入门篇对Python做了介绍并结合金融场景演示了Python的基本操作;基础篇结合金融场景,讲解NumPy、Pandas、Matplotlib、SciPy等Python模块的具体运用;提高篇详细讨论运用Python分析利率、债券、股票、期货、期权以及风险价值等内容。
本书是专注于Python在金融领域运用的普及性读物,作者斯文博士在金融与风险管理方面有着深厚的积累,同时也有着丰富的编程经验,一直致力于倡导和推广Python在金融领域的运用。
本书适合想要掌握Python应用的金融学习者、金融从业者阅读,也适合想要转行到金融领域的程序员以及对Python在金融领域的实践应用感兴趣的人士阅读,并且不要求读者有Python编程基础。
Author Description

斯文,笔名“华尔街先生”,浙江湖州人,经济学博士,中国注册会计师(Certified Public Accountant,CPA),特许金融分析师(Chartered Financial Analyst,CFA),金融风险管理师(Financial Risk Manager,FRM)。在国内某金融控股集团担任高级风控总监,拥有在中外资银行、证券公司、信托公司等机构十余年的金融与风险管理从业经验。
同时,他也是上海财经大学风险管理校友俱乐部的发起人兼理事长、《上财风险管理论坛》杂志主编、上海资产管理行业风险管理同业交流会秘书长,并担任中南财经政法大学、华东政法大学等多所国内高校的金融硕士研究生兼职导师,公开发表学术论文50 余篇,出版了专著《中国外汇衍生品市场研究》(上海人民出版社2016 年8 月出版),多次荣获***、省部级的荣誉称号。
除此之外,他还历时3 年多推出了《期权、期货及其他衍生产品(第九版)》视频课程(共360讲),累计观看人次超过百万,累计撰写了10万多行与金融相关的Python 代码,长期致力于倡导并推广Python在金融领域的运用。
Catalogue

第 1部分入门篇

第1章 Python概览2
1.1Python的定义与比较优势3
1.1.1Python简介3
1.1.2Python的比较优势4
1.2Python之父—吉多·范罗苏姆5
1.3Python的演进历史和常用版本7
1.4Python的安装8
1.4.1单独安装8
1.4.2集成安装8
1.4.3安装并启动Anaconda9
1.4.4Spyder的界面12
1.5学习Python的方法论13
1.5.1学习的态度13
1.5.2学习的原则13
1.5.3学习的方法14
1.6金融数据的获取15
1.6.1万得(Wind)15
1.6.2同花顺15
1.6.3CCER经济金融数据库15
1.6.4国泰安经济金融研究数据库16
1.7小结16
1.8拓展阅读16
第2章 结合金融演示Python的基本
操作17
2.1金融变量在Python中的赋值18
2.2Python的数据类型18
2.2.1整型19
2.2.2浮点型19
2.2.3复数20
2.2.4字符串20
2.3Python的数据结构23
2.3.1元组23
2.3.2列表25
2.3.3集合28
2.3.4字典30
2.4Python的运算符号33
2.4.1基本算术运算符号33
2.4.2关系运算符号36
2.4.3赋值运算符号37
2.4.4成员运算符号38
2.5Python的主要内置函数39
2.6自定义函数43
2.6.1运用def语法43
2.6.2运用lambda函数44
2.7Python的语句44
2.7.1条件语句44
2.7.2循环语句46
2.7.3条件语句和循环语句结合48
2.8模块的导入与math模块49
2.8.1模块导入的若干种方法50
2.8.2math模块51
2.9小结53
2.10拓展阅读53

第2部分 基础篇

第3章结合金融场景演示NumPy
模块的操作56
3.1从一个投资案例讲起57
3.2N维数组58
3.2.1数组的结构58
3.2.2数组的便捷生成60
3.3数组的索引、切片和排序63
3.3.1索引63
3.3.2切片64
3.3.3排序64
3.4数组的相关运算65
3.4.1数组内的运算65
3.4.2数组间的运算69
3.4.3矩阵的操作72
3.5通过NumPy生成随机数74
3.5.1主要的统计分布74
3.5.2主要函数80
3.5.3相关示例82
3.6小结85
3.7拓展阅读86
第4章结合金融时间序列演示Pandas
模块的操作87
4.1Pandas的数据结构88
4.1.1序列88
4.1.2数据框90
4.1.3外部数据导入并直接生成
数据框91
4.2数组框的可视化93
4.2.1中文字体的可视化93
4.2.2数据框可视化的函数与参数94
4.2.3一个示例95
4.3数据框内部的操作96
4.3.1描述数据框的基本性质96
4.3.2数据框的索引与截取98
4.3.3数据框的排序100
4.3.4数据框的更改102
4.4数据框之间的操作105
4.4.1生成两个新的数据框105
4.4.2函数concat的运用106
4.4.3函数merge的运用108
4.4.4函数join的运用109
4.5数组框的主要统计函数109
4.5.1静态的统计函数110
4.5.2移动窗口与动态统计函数114
4.6小结117
4.7拓展阅读117
第5章结合金融场景演示Matplotlib
模块的操作118
5.1基本函数119
5.2曲线图122
5.2.1单一曲线图123
5.2.2多图绘制124
5.3直方图126
5.3.1单一样本的直方图126
5.3.2多个样本的直方图128
5.4条形图129
5.4.1垂直条形图130
5.4.2水平条形图132
5.5散点图133
5.6饼图136
5.7小结138
5.8拓展阅读138
第6章结合金融场景演示SciPy等
模块的操作139
6.1SciPy模块140
6.1.1求积分141
6.1.2插值法142
6.1.3求解方程组144
6.1.4最优化求解146
6.1.5统计功能150
6.2StatsModels模块156
6.3波动率模型与arch模块159
6.3.1估计波动率159
6.3.2ARCH模型160
6.3.3GARCH模型161
6.3.4arch模块163
6.4datetime模块167
6.4.1创建时间的对象168
6.4.2访问时间对象的属性169
6.4.3时间对象的运算169
6.5小结171
6.6拓展阅读171



第3部分提高篇

第7章运用Python分析利率与债券174
7.1利率体系175
7.1.1中央银行利率175
7.1.2金融机构利率177
7.1.3金融市场利率179
7.2债券市场182
7.2.1债券交易场所183
7.2.2债券品种185
7.3利率的度量188
7.3.1利率的复利频次189
7.3.2连续复利192
7.3.3零息利率194
7.4债券定价与债券收益率195
7.4.1债券的核心要素195
7.4.2基于单一贴现率的债券定价195
7.4.3债券到期收益率196
7.4.4基于不同期限贴现率的债券
定价197
7.4.5通过票息剥离法计算零息
利率198
7.4.6运用零息利率对债券定价203
7.5远期利率与远期利率协议204
7.5.1远期利率204
7.5.2远期利率协议207
7.6衡量债券利率风险的线性指标—
久期211
7.6.1麦考利久期212
7.6.2修正久期214
7.6.3美元久期217
7.7衡量债券利率风险的非线性
指标—凸性218
7.7.1凸性的表达式219
7.7.2案例219
7.7.3重要关系式220
7.8小结221
7.9拓展阅读221
第8章运用Python分析股票投资222
8.1股票市场简介223
8.1.1多层次股票市场223
8.1.2主要的股票指数225
8.2股票投资组合228
8.2.1投资组合的主要变量229
8.2.2投资组合的有效前沿235
8.2.3资本市场线239
8.3资本资产定价模型241
8.3.1系统风险与非系统风险241
8.3.2模型数学表达式及运用245
8.4股价服从的随机过程249
8.4.1马尔可夫过程与有效市场假说249
8.4.2维纳过程与广义维纳过程251
8.4.3几何布朗运动253
8.5投资组合的绩效评估259
8.5.1夏普比率259
8.5.2索提诺比率262
8.5.3特雷诺比率264
8.5.4信息比率266
8.6小结268
8.7拓展阅读269
第9章运用Python分析期货套期
保值270
9.1期货市场的简介271
9.1.1期货交易所及合约品种271
9.1.2股指期货合约的介绍275
9.1.3国债期货合约的介绍277
9.1.4参与期货交易的动机279
9.2股指期货的套期保值280
9.2.1套期保值的类型280
9.2.2追加保证金的风险282
9.2.3基差风险285
9.2.4交叉套期保值289
9.3国债期货合约的套期保值297
9.3.1计息天数规则298
9.3.2国债的报价300
9.3.3国债期货最终价格301
9.3.4国债期货的最廉价交割304
9.3.5基于久期的套期保值策略307
9.4小结310
9.5拓展阅读310
第10章 运用Python分析期权的
定价与风险311
10.1A股股票期权市场简介312
10.1.1权证市场312
10.1.2股指期权合约313
10.2期权类型和到期时的盈亏315
10.2.1期权的类型和要素315
10.2.2看涨期权到期时的盈亏316
10.2.3看跌期权到期时的盈亏318
10.2.4看跌-看涨平价关系式320
10.3布莱克-斯科尔斯-默顿模型323
10.4期权价格与相关变量的关系325
10.4.1期权价格与基础资产价格的
关系325
10.4.2期权价格与执行价格的关系326
10.4.3期权价格与波动率的关系327
10.4.4期权价格与无风险收益率的
关系328
10.4.5期权价格与期权期限的关系330
10.5衡量期权的风险—希腊字母331
10.5.1期权的Delta331
10.5.2期权的Gamma335
10.5.3期权的Theta339
10.5.4期权的Vega343
10.5.5期权的Rho347
10.6期权的隐含波动率351
10.6.1运用牛顿迭代法计算隐含
波动率351
10.6.2运用二分查找法计算隐含
波动率353
10.7波动率微笑与斜偏355
10.7.1波动率微笑355
10.7.2波动率斜偏358
10.8小结362
10.9拓展阅读362
第11章 运用Python分析期权交易
策略363
11.1保本票据364
11.1.1一个虚拟的案例364
11.1.2一个真实市场的案例366
11.2单一期权与单一基础资产的策略368
11.2.1买入备兑看涨期权369
11.2.2卖出备兑看涨期权371
11.2.3买入保护看跌期权373
11.2.4卖出保护看跌期权375
11.2.5策略的期间收益377
11.3价差交易策略381
11.3.1牛市价差策略381
11.3.2熊市价差策略385
11.3.3盒式价差策略389
11.3.4蝶式价差策略392
11.4组合策略397
11.4.1跨式组合策略397
11.4.2序列组合策略与带式组合
策略401
11.4.3宽跨式组合策略404
11.5小结412
11.6拓展阅读412
第12章 运用Python测度风险价值413
12.1风险价值的概述414
12.1.1风险价值的定义414
12.1.2运用Python对风险价值
可视化415
12.1.3风险价值的优点与局限性417
12.2风险价值的方差-协方差法418
12.2.1方差-协方差法的简介418
12.2.2案例420
12.3风险价值的历史模拟法423
12.3.1历史模拟法的简介423
12.3.2案例425
12.4蒙特卡罗模拟法428
12.4.1蒙特卡罗模拟的简介428
12.4.2案例430
12.5回溯检验、压力测试与压力风险
价值434
12.5.1回溯检验434
12.5.2压力测试437
12.5.3压力风险价值439
12.5.4比较不同方法计算的风险
价值443
12.6小结443
12.7扩展阅读443
后记445

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Yami has a consolidation warehouse in China which collects multiple sellers’ packages and combines to one order. Our Yami consolidation warehouse will directly ship the packages to your door. Cross-store free shipping over $69.

Return Policy

You may return products within 30 days upon receiving the products. Sellers take responsibilities for any wrong shipment or missing items. Packing needs to be unopened for any other than quality issues return. We promise to pack carefully, but because goods are taking long journey to destinations, simple damages to packaging may occur. Any damages not causing internal goods quality problems are not allowed to return. If you open the package and any quality problem is found, please contact customer service within three days after receipt of goods.

Shipping Information

Yami Consolidation Service Shipping Fee $9.99(Free shipping over $69)

Sellers in China will ship their orders within 1-2 business days once the order is placed. Packages are sent to our consolidation warehouse in China and combined there. Our Yami consolidation warehouse will directly ship the packages to you via UPS. The average time for UPS to ship from China to the United States is about 10 working days and it can be traced using the tracking number. Due to the pandemic, the delivery time may be delayed by about 5 days. The package needs to be signed by the guest. If the receipt is not signed, the customer shall bear the risk of loss of the package.

Sold by JD@CHINA

Service Guarantee

Free shipping over 69
Genuine guarantee

Shipping

Yami Consolidated Shipping $9.99(Free shipping over $69)


Seller will ship the orders within 1-2 business days. The logistics time limit is expected to be 7-15 working days. In case of customs clearance, the delivery time will be extended by 3-7 days. The final receipt date is subject to the information of the postal company.

Yami Points information

All items are excluding from any promotion or points events on Yamibuy.com

Return Policy

You may return product within 30 days upon receiving the product. Items returned must be new in it's original packing, including the original invoice for the purchase. Customer return product at their own expense.

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About the brand

Jingdong book

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About the brand

Jingdong book