Got the book in the mail yesterday and going through it. They just added an LMM model to QuantLib and since I know nothing about fixed rate income derivative pricing, the book is useful. The thing that I like most about it is that the first section has a historical overview that explains the false starts and dead ends, that got us to where we are.
I’ve always wished that intro science courses had more information about how messy science is with its false starts and dead ends, and I tried to put that knowledge into my intro astronomy course at UoP and into my contributions to Wikitext (look at Roadrunner’s edits to the Intro astronomy text.) This is so that people understand how tenative out knowledge is, and one of the themes of these articles is that a power system that portrays those with power as all-knowing is not good even for those in power.
But as a newbie, I like reading the context, it makes me believe I can do something useful to add to it. The problem is that I’m outside of the important social networks, which is a topic for another blog.
The other good thing about the book is that it is written with a lot of the style of Mark Joshi’s books on C++. A lot of text. This is closer to physicist language, than mathematician language. Most non-scientists don’t realize how different the world looks to a physicist than a mathematician, and I’ve always found too many Greek symbols to be a little intimidating. I can read a paper that says “Theorem 1” followed by pages of Greek rigourously derivative another set of pages of Greek symbols, but I can’t write a paper like that, and I’m not thinking in Greek, I’m thinking in physical metaphor.
The problem with the book is that I can’t see the connection to Mainland Chinese derivatives. Shanghai doesn’t have any complex fixed income instruments. (I don’t know anything about the Hong Kong markets). On the other hand, it is important for me understand the language. Let me just sit down with the book for about a month.