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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 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

Checking the existence of our functions

Again, we can use the dir() function to detect the existence of our just covered pv_f() function, as shown in the following code:

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

To save our file, we need to perform the following simple steps:

  1. Navigate to File | New Window Ctrl + N and type the following two-liner code. A careful user would notice that after pressing the Enter key at the end of the first line, the second line will be indented automatically. While writing just two lines of code, it is not obvious. However, for a block of code with multiple lines, a correct indentation is critical. Later in the chapter, we will show and discuss this issue in more detail:
    def pv_f(fv,r,n):
        return fv/(1+r)**n
    
  2. Click on File and then save (Ctrl + S) to save the preceding two lines of code. Assume that we name the file as test01.py. The default directory is Python33 in C:...
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