QuantLib Python Cookbook

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About

The book collects updated posts from Goutham's blog and the transcripts of the screencasts that Luigi published on YouTube.

The posts and screencasts use Jupyter notebooks to demonstrate the QuantLib library. Together, they provide a sort of cookbook that showcases features of the library by means of working examples and provides guidance to its use.

Among other content, the book also includes notebooks that reproduce the results from the often-cited Ametrano and Bianchetti paper, Everything You Always Wanted to Know About Multiple Interest Rate Curve Bootstrapping but Were Afraid to Ask.

More updated content is available in the new book A QuantLib Guide.

If you're interested in the architecture of QuantLib and want to know how to extend it, you might want to look at Implementing QuantLib, too.

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Author

Goutham Balaraman

Goutham Balaraman is the Chief Technology Officer at Crossroads Equipment Lease & Finance. Prior to that he held leadership positions at various financial services and FinTech organizations such as Cartiga, loanDepot, Numerix and ICE. He holds a Ph.D. in Theortical Physics from Georgia Institute of Technology, USA. He writes about technology topics at https://leadwithtech.com.

A note on Python and C++

Code conventions used in this book

IBasics

1.QuantLib basics

2.Instruments and pricing engines

3.Numerical Greeks calculation

4.Market quotes

5.Term structures and their reference dates

6.Pricing over a range of days

7.A note on random numbers and dimensionality

IIInterest-rate curves

8.EONIA curve bootstrapping

9.Euribor curve bootstrapping

10.Constructing a yield curve

11.Dangerous day-count conventions

12.Implied term structures

13.Interest-rate sensitivities via zero spread

14.A glitch in forward-rate curves

IIIInterest-rate models

15.Simulating interest rates using Hull White model

16.Thoughts on the convergence of Hull-White model Monte Carlo simulations

17.Short interest rate model calibration

18.Par versus indexed coupons

19.Modeling interest rate swaps using QuantLib

20.Caps and floors

IVEquity models

21.Valuing European option using the Heston model

22.Volatility smile and Heston model calibration

23.Heston model parameter calibration in QuantLib Python & SciPy

24.Valuing European and American options

25.Valuing options on commodity futures using the Black formula

26.Defining rho for the Black process

27.Using curves with different day-count conventions

VBonds

28.Modeling fixed rate bonds

29.Building irregular bonds

30.Valuation of bonds with credit spreads

31.Modeling callable bonds

32.Discount margin calculation

33.Duration of floating-rate bonds

34.Treasury futures contracts

35.Mischievous pricing conventions

36.More mischievous conventions

Appendix

Translating QuantLib Python examples to C++

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