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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

Chapter 9. The Black-Scholes-Merton Option Model

In modern finance, the option theory and its applications play an important role. Many trading strategies, corporate incentive plans, and hedging strategies include various types of options. In Chapter 6, Introduction to NumPy and SciPy, we showed that you can write a five-line Python program to price a call option based on the Black-Scholes-Merton option model even without understanding its underlying theory and logic. In this chapter, we will explain the option theory and its related applications in more detail.

In particular, we will cover the following topics:

  • Payoff and profit/loss functions and their graphical representations of call and put
  • European versus American options
  • Normal distribution, standard normal distribution, and cumulative normal distribution
  • The Black-Scholes-Merton option model with/without dividend
  • Various trading strategies and their visual presentations, such as covered call, straddle, butterfly, and calendar...
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