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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

Chapter 4. 13 Lines of Python to Price a Call Option

To many readers, option theory is like rocket science. In order to make option theory less intimidating, we deliberately avoided any mathematical formula in this chapter. Literally, the focus of the whole chapter is around 13 lines of Python code. An option buyer pays to acquire the right to buy (or sell) something in the future while an option seller receives an upfront payment to bear an obligation to sell to (or buy from) the option buyer. A call option buyer has the right to buy a stock at a fixed price and at a fixed date in the future. A European option can only be exercised when the option expires, while an American option could be exercised any time before or at the maturity date.

In this chapter, we will cover the following topics:

  • 13 lines of Python code to price a call option
  • Writing a Python function without saving it
  • Using the empty shell method to write a complex Python program
  • Using the comment-all-out method to write...
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