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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

Forward rates


An investor who plans to invest at a later time might be curious to know what the future interest rate might look like, as implied by today's term structure of interest rates. For example, you might ask: What is the one-year spot rate one year from now? To answer this question, one can calculate forward rates for the period between and using this formula:

Here, and are the continuously compounded annual interest rates at time period and respectively.

The following Python code helps us generate a list of forward rates from a list of spot rates:

"""
Get a list of forward rates
starting from the second time period
"""


class ForwardRates(object):
    
    def __init__(self):
        self.forward_rates = []
        self.spot_rates = dict()
        
    def add_spot_rate(self, T, spot_rate):
        self.spot_rates[T] = spot_rate
    
    def __calculate_forward_rate___(self, T1, T2):
        R1 = self.spot_rates[T1]
        R2 = self.spot_rates[T2]
        forward_rate = (R2...
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