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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 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

Finding out more information about a specific built-in function

To understand each math function, we apply the help() function, such as help(round), as shown in the following example:

>>>help(round)
Help on built-in function round in module builtins:
round(...)
    round(number[, ndigits]) -> number
Round a number to a given precision in decimal  
digits (default 0 digits).This returns an int when 
called with one argument, otherwise the same type as 
the number. ndigits may be negative.

Listing all built-in functions

To find out all built-in functions, we perform the following two-step approach. First, we issue dir() to find the default name that contains all default functions. When typing its name, be aware that there are two underscores before and another two underscores after the letters of builtins, that is, __builtins__:

>>>dir()
['__builtins__', '__doc__', '__loader__', '__name__', '__package__', 'x']...
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