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Mastering Python for Finance

You're reading from   Mastering Python for Finance Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784394516
Length 340 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Python for Financial Applications FREE CHAPTER 2. The Importance of Linearity in Finance 3. Nonlinearity in Finance 4. Numerical Procedures 5. Interest Rates and Derivatives 6. Interactive Financial Analytics with Python and VSTOXX 7. Big Data with Python 8. Algorithmic Trading 9. Backtesting 10. Excel with Python Index

Bond convexity


Convexity is the sensitivity measure of the duration of a bond to yield changes. Think of convexity as the second derivative of the relationship between the price and yield:

Bond traders use convexity as a risk management tool to measure the amount of market risk in their portfolio. Higher convexity portfolios are less affected by interest rate volatilities than lower convexity portfolio, given the same bond duration and yield. As such, higher convexity bonds are more expensive than lower convexity ones, everything else being equal.

The implementation of a bond convexity is given as follows:

""" Calculate convexity of a bond """
from bond_ytm import bond_ytm
from bond_price import bond_price


def bond_convexity(price, par, T, coup, freq, dy=0.01):
    ytm = bond_ytm(price, par, T, coup, freq)

    ytm_minus = ytm - dy    
    price_minus = bond_price(par, T, ytm_minus, coup, freq)
    
    ytm_plus = ytm + dy
    price_plus = bond_price(par, T, ytm_plus, coup, freq)
    
  ...
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