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Python for Finance

You're reading from   Python for Finance If your interest is finance and trading, then using Python to build a financial calculator makes absolute sense. As does this book which is a hands-on guide covering everything from option theory to time series.

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Product type Paperback
Published in Apr 2014
Publisher
ISBN-13 9781783284375
Length 408 pages
Edition 1st Edition
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (14) Chapters Close

Preface 1. Introduction and Installation of Python FREE CHAPTER 2. Using Python as an Ordinary Calculator 3. Using Python as a Financial Calculator 4. 13 Lines of Python to Price a Call Option 5. Introduction to Modules 6. Introduction to NumPy and SciPy 7. Visual Finance via Matplotlib 8. Statistical Analysis of Time Series 9. The Black-Scholes-Merton Option Model 10. Python Loops and Implied Volatility 11. Monte Carlo Simulation and Options 12. Volatility Measures and GARCH Index

Why Python?

There are various reasons that Python should be used. Firstly, Python is free in terms of license. Python is available for all major operating systems, such as Windows, Linux/Unix, OS/2, Mac, and Amiga, among others. Being free has many benefits. When students graduate, they could apply what they have learned wherever they go. This is true for the financial community as well. In contrast, this is not true for SAS and MATLAB. Secondly, Python is powerful, flexible, and easy to learn. It is capable of solving almost all our financial and economic estimations. Thirdly, we could apply Python to Big Data. Dasgupta (2013) argues that R and Python are two of the most popular open source programming languages for data analysis. Fourthly, there are many useful modules in Python. Each model is developed for a special purpose. In this book, we focus on NumPy, SciPy, Matplotlib, Statsmodels, and Pandas modules.

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