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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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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 (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Introduction to credit risk analysis

In this chapter, we will discuss basic concepts related to credit risk, such as credit rating, credit spread, 1-year and 5-year rating migration matrices, probability of default, recovery rate, and loss given default. A credit spread, the difference between a bond's yield and a benchmark yield (risk-free rate), reflects its credit risk or default risk. For example, to estimate the present value of a coupon payment in two years for an AA rated bond, the discount rate (yield) will be a risk-free yield (treasury-note yield) plus the corresponding spread. There are many tools that we could use when analyzing a company or a bond's credit worthiness. The first tool is credit rating offered by a credit rating agent, such as Moody's or Standard and Poor's. One of the apparent advantages is that a potential user would spend less time and efforts to assess a company or a bond's credit risk. The obvious disadvantage is that the credit...

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