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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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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction and Installation of Python 2. Using Python as an Ordinary Calculator FREE CHAPTER 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

Importing the math module

When learning finance with real-world data, we deal with many issues such as downloading data from Yahoo! finance, choosing an optimal portfolio, estimating volatility for individual stocks or for a portfolio, and constructing an efficient frontier. For each subject (topic), experts develop a specific module (package). To use them, we have to import them. For example, we can use import math to import all basic math functions. In the following codes, we calculate the square root of a value:

>>>import math
>>>math.sqrt(3)
1.732050807568772

To find out all functions contained in the math module, we call the dir() function again as follows:

>>>import math
>>>dir(math)
['__doc__', '__loader__', '__name__', '__package__', 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'ceil', 'copysign', &apos...
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Python for Finance
Published in: Apr 2014
Publisher:
ISBN-13: 9781783284375
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