Python金融大數(shù)據(jù)分析（第2版 影印版）
定 價(jià)：158 元
- 作者：Yves，Hilpisch 著
- 出版時(shí)間：2019/6/1
- ISBN：9787564183721
- 出 版 社：東南大學(xué)出版社
- 中圖法分類(lèi)：F830.41-39
- 頁(yè)碼：691
- 紙張：膠版紙
- 版次：1
- 開(kāi)本：16開(kāi)
Python已成為數(shù)據(jù)驅(qū)動(dòng)和AI優(yōu)先的金融界的編程語(yǔ)言。一些投資銀行和對(duì)沖基金現(xiàn)在都使用Python及其生態(tài)系統(tǒng)來(lái)構(gòu)建核心交易和風(fēng)險(xiǎn)管理系統(tǒng)。
在《Python金融大數(shù)據(jù)分析（第2版 影印版）》的第二版中，YvesHilpisch向開(kāi)發(fā)人員和定量分析師展示了如何使用Python包和工具進(jìn)行金融數(shù)據(jù)科學(xué)、算法交易和計(jì)算金融學(xué)。第二版針對(duì)Python3進(jìn)行了更新，其中的大部分代碼都采用了JupyterNotebooks的形式，為幾乎所有的示例提供了可執(zhí)行交互式版本。在共5部分內(nèi)容中，你將學(xué)習(xí)到Python及其生態(tài)系統(tǒng)是如何為從事金融業(yè)務(wù)的公司和個(gè)人提供技術(shù)框架的。
Yves Hilpisch，The Python Quans的創(chuàng)始人和任事股東，該集團(tuán)專(zhuān)注于用于金融數(shù)據(jù)科學(xué)、人工智能、算法交易和計(jì)算金融的開(kāi)源技術(shù)的使用。他也是The AI Machine的創(chuàng)始人和CEO，該公司專(zhuān)注于利用通過(guò)專(zhuān)有策略執(zhí)行平臺(tái)進(jìn)行的算法交易的人工智能的力量。Yves還是最終成為University Certificatein Python for Algorithmic Trading的首位在線培訓(xùn)計(jì)劃的負(fù)責(zé)人。
Preface
Part 1．Python and Finance
1． Why Python for Finance
The Python Programming Language
A Brief History of Python
The Python Ecosystem
The Python User Spectrum
The Scientific Stack
Technology in Finance
Technology Spending
Technology as Enabler
Technology and Talent as Barriers to Entry
Ever-Increasing Speeds， Frequencies， and Data Volumes
The Rise of Real-Time Analytics
Python for Finance
Finance and Python Syntax
Efficiency and Productivity Through Python
From Prototyping to Production
Data-Driven and AI-First Finance
Data-Driven Finance
AI-First Finance
Conclusion
Further Resources
2． Python Infrastructure
conda as a Package Manager
Installing Miniconda
Basic Operations with conda
conda as a Virtual Environment Manager
Using Docker Containers
Docker Images and Containers
Building an Ubuntu and Python Docker Image
Using Cloud Instances
RSA Public and Private Keys
Jupyter Notebook Configuration File
Installation Script for Python and Jupyter Notebook
Script to Orchestrate the Droplet Setup
Conclusion
Further Resources
Part II．Mastering the Basics
3． Data Types and Structures
Basic Data Types
Integers
Floats
Booleans
Strings
Excursion： Printing and String Replacements
Excursion： Regular Expressions
Basic Data Structures
Tuples
Lists
Excursion： Control Structures
Excursion： Functional Programming
Dicts
Sets
Conclusion
Further Resources
4． Numerical Computing with NumPy
Arrays of Data
Arrays with Python Lists
The Python array Class
Regular NumPy Arrays
Part III． Financial data science
Part IV． Algorithmic Trading
Part V． Derivatives Analytics
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