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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

Exotic options

Up to now, we discussed European and American options in Chapter 9, The Black-Scholes-Merton Option Model, which are also called vanilla options. One of the characters is path independent. On the other hand, exotic options are more complex since they might have several triggers relating to the determination of their payoffs. An exotic option could include nonstandard underlying instrument developed for particular investors, banks, or firms. Exotic options usually are traded over-the-counter (OTC). For exotic options, we don't have closed-form solutions, such as the Black-Scholes-Merton model. Thus, we have to depend on other means to price them. The Monte Carlo simulation is one of the ways to price many exotic options. In the next several subsections, we show how to price Asian options, digit options, and barrier options.

Using the Monte Carlo simulation to price average options

European and American options are path-independent options. This means that an option&apos...

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