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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

Using and debugging other programs

Quite often than not, we might start our project based on a program or programs written by others, such as the programs by our fellow researchers, other students, teachers, programs downloaded from the Internet, or the old programs we wrote ourselves a long time ago. As the first step, we need to know whether our borrowed program contains any errors. These two methods could be used to debug such a program. In a sense, the second method, comment-all-out method, is preferred since it might save us some typing or copy-and-paste time. To debug other programs, the key is to find the locations of the errors. Here is a very useful Python program to get data from Yahoo! Finance: http://goldb.org/ystockquote.html. A beginner could download the program to try small functions contained in the program.

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