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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

Constructing an efficient frontier

In finance, constructing an efficient frontier is always a challenging job. This is especially true with real-world data. In this section, we discuss the estimation of a variance-covariance matrix and its optimization, finding an optimal portfolio, and constructing an efficient frontier with stock data downloaded from Yahoo! Finance.

Estimating a variance-covariance matrix

When a return matrix is given, we could estimate its variance-covariance matrix. For a given set of weights, we could further estimate the portfolio variance. The formulae to estimate the variance and standard deviation for returns from a single stock are given as follows:

Estimating a variance-covariance matrix
Estimating a variance-covariance matrix

Here, Ri is the stock return for period i, Estimating a variance-covariance matrix is their mean, and n is the number of the observations. For an n-stock portfolio, we have the following formulae:

Estimating a variance-covariance matrix

The variance of a two-stock portfolio is given as follows:

Estimating a variance-covariance matrix

Here, Estimating a variance-covariance matrix is the covariance between stocks 1 and 2, Estimating a variance-covariance matrix is the correlation coefficient between stocks 1 and 2...

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