Mastering Python for Finance

Weiming, James Ma

ISBN 10: 1784394513 / ISBN 13: 9781784394516

Edité par Packt Publishing, 2015

A propos de cet article

Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

N° de réf. du vendeur 00088208180

Détails bibliographiques

• Titre: Mastering Python for Finance
• Éditeur: Packt Publishing
• Date de parution: 2015
• Langue: anglais
• ISBN à 10 chiffres: 1784394513
• ISBN à 13 chiffres: 9781784394516
• Reliure: Couverture souple
• État de l'article: Very Good

A propos de ce titre

Synopsis

Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

Key Features:

• Explore financial models used by the industry and ways of solving them with this guide
• Discover the various features that Python provides for scientific computing and harness them to enhance your financial applications
• Build state-of-the-art infrastructure for critical aspects such as modeling, trading, pricing, and analytics

Book Description:

Built initially for scientific computing, Python quickly found its place in finance. Its flexibility and robustness can be easily incorporated into applications for mathematical studies, research, and software development.

With this book, you will learn about all the tools you need to successfully perform research studies and modeling, improve your trading strategies, and effectively manage risks. You will explore the various tools and techniques used in solving complex problems commonly faced in finance.

You will learn how to price financial instruments such as stocks, options, interest rate derivatives, and futures using computational methods. Also, you will learn how you can perform data analytics on market indexes and use NoSQL to store tick data.

What You Will Learn:

• Perform interactive computing with IPython Notebook
• Solve linear equations of financial models and perform ordinary least squares regression
• Explore nonlinear modeling and solutions for optimum points using root-finding algorithms and solvers
• Discover different types of numerical procedures used in pricing options
• Model fixed-income instruments with bonds and interest rates
• Manage big data with NoSQL and perform analytics with Hadoop
• Build a high-frequency algorithmic trading platform with Python
• Create an event-driven backtesting tool and measure your strategies

À propos de l?auteur

James Ma Weiming

James Ma Weiming works with high-frequency, low-latency trading systems, writing his own programs and tools, most of which are open sourced. He is currently supporting veteran traders in the, trading pits of the Chicago Board of Trade devising strategies to game the market. He graduated from the Stuart School of Business at Illinois Institute of Technology with a master of science degree in finance. He started his career in Singapore after receiving his bachelor's degree in computer engineering from Nanyang Technological University and diploma in information technology from Nanyang Polytechnic. During his career, he has worked in treasury operations handling foreign exchange and fixed income products. He also developed mobile applications with a company operating a funds and investments distribution platform.