## Book description

The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics.

Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.

## Publisher resources

## Table of contents

- Preface
- I. Python and Finance
- 1. Why Python for Finance
- 2. Python Infrastructure
- II. Mastering the Basics
- 3. Data Types and Structures
- 4. Numerical Computing with NumPy
- 5. Data Analysis with pandas
- 6. Object-Oriented Programming
- III. Financial Data Science
- 7. Data Visualization
- 8. Financial Time Series
- 9. Input/Output Operations
- 10. Performance Python
- 11. Mathematical Tools
- 12. Stochastics
- 13. Statistics
- IV. Algorithmic Trading
- 14. The FXCM Trading Platform
- 15. Trading Strategies
- 16. Automated Trading
- V. Derivatives Analytics
- 17. Valuation Framework
- 18. Simulation of Financial Models
- 19. Derivatives Valuation
- 20. Portfolio Valuation
- 21. Market-Based Valuation
- A. Dates and Times
- B. BSM Option Class
- Index

## Product information

- Title: Python for Finance, 2nd Edition
- Author(s):
- Release date: December 2018
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492024330

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