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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
Languages
Tools
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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 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

Importing a module

Assume that we want to estimate the square root of the number three. However, after issuing the following lines of code, we would encounter an error message:

>>>sqrt(3)
SyntaxError: invalid syntax
>>>

The reason is that the sqrt() function is not a built-in function. To use the sqrt() function, we need to import the math module first as follows:

>>>import math
>>>x=math.sqrt(3)
>>>round(x,4)
1.7321

To use the sqrt() function, we have to type math.sqrt() if we use the import math command to upload the math module. In addition, after issuing the command dir(), we will see the existence of the math module, which is the last one in the output shown as follows:

>>>dir()
['__builtins__', '__doc__', '__name__', '__package__', 'math']

In addition, when a module is reinstalled, we could use import x_module to upload it. For instance, the math module is a built-in module, and it...

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