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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

Exercises

1. What is the difference between an American call and a European call?

2. What is the unit of rf in the Black-Scholes-Merton option model?

3. If we are given the annual rate of 3.4 percent, compounded semi-annually, what will the value of rf be that we should use for the Black-Scholes-Merton option model ?

4. How do we use options to hedge?

5. How do we treat predetermined cash dividends to price a European call?

6. Why is an American call worth more than a European call?

7. Assume you are a mutual fund manager and your portfolio's β is strongly correlated with the market. You are worried about the short-term fall in the market. What you could do to protect your portfolio?

8. The current price of stock A is $38.5 and the strike prices for a call and a put options are both $37. If the continuously compounded risk-free rate is 3.2 percent, maturity is six months, and the volatility of stock A is 0.25, what are the prices for a European call and put?

9. Use the put-call parity...

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