David Backus and Stanley Zin
Advanced Fixed Income Analytics for Financial Professionals
(B40.3176.33, Spring 1999)
What is the course about?
- Quantitative models play an increasingly important role in
the financial services industry ---
valuation, trading, structuring, and risk management.
In this course, you will learn how such models are built and used,
put them to work yourself using proprietary software,
develop insights into their strengths and weaknesses,
and hear from experts about industry best practice.
-
Our approach to modeling introduces state-of-the-art
structure with relatively modest technical requirements.
Make no mistake: this is a quantitative course.
But the level of mathematics rarely rises as high as high school calculus.
Our approach includes discrete time and continuous states.
In our view, this is both
a marked improvement in accuracy over the binomial models
typically used in most MBA classes
and a substantial gain in simplicity over the stochastic calculus
of most high-end financial theory.
-
Free to students in the course is a set of custom software
that can be used to build models,
adjust parameter values,
and value a variety of fixed income derivatives:
caps and floors, swaptions, eurocurrency futures, and so on.
Essential information
- Prerequisite: B40.3333 Debt Instruments and Markets
or the equivalent expertise from other sources.
- Meetings: Wednesdays, 5:30 to 8:20 pm, March 10 to April 28 (not March 17),
MEC 5-90.
- Files are pdf format unless stated otherwise.
To view or print pdf files,
visit
Adobe's Web Site to get Adobe's Acrobat Reader.
Once installed, the Reader pops up in Netscape when you click on a pdf file,
allowing you to view and print the file.
For obscure reasons, the files print better than they look on the screen.
To print postscript files, click on the file,
choose Save As to copy to your hard drive, then print however you like
(I type this in DOS: copy file lpt1).
You can also download a postscript viewer (Ghostview).
- Essential course material
Useful Links
Please address comments and questions to Dave Backus
(dbackus@stern.nyu.edu)
or Stan Zin
(szin@stern.nyu.edu)
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