huntse
What about this one? Look like someone making mistakes in introductory drawing class to you? http://www.art-wallpaper.com/4056/C%C3%A9zanne+Paul/Sketch+a...
How about this? Beginner rendering perhaps? http://amica.davidrumsey.com/luna/servlet/detail/AMICO~1~1~3...
The problem is you can't quite bring yourself to admit that you picked a really bad example. You wanted someone who's technical deficiencies were made up for by their conceptual skill, and you chose someone who could draft their ass off and also had an incredible ability to choose fantastic things to produce.
Oh, and for goodness sake don't put down on your cv that you've read the first 13 chapters of Hull and know Ito's Lemma and the Black Scholes model. (Unless you just want to give people a good chuckle.)
If you really want to bone up on your financial maths with a bias towards a job in computational finance I always recommend people read Joshi. http://www.markjoshi.com/
Our development cycle is super fast, yet I work on very sensitive applications and infrastructure (real time trading, pricing, risk etc).
Bottom line: Jobs vary significantly in any industry and within any firm.
The coupon stream on mezz notes can be linked to income on specific assets (like covered bonds).
Subordinated debt and preferred shares are examples of mezz finance instruments.
Now to the first point. The most important part of learning is the process itself: ie learning the thing itself is less important than becoming good at learning. Once you have a sound grasp of the basics, the more diverse your curiosity and the deeper the insight you are able to gain into each specific technology, the easier it will be for you to pick up new ones. There's no excuse for ever becoming obsolete. Read widely, maintain your curiosity and keep learning.
Finally, the technologies you have picked may or may not be the way of the future. The future has a way of being unpredictable. Don't be so sure that you know what is going to happen that you close your eyes to what is actually happening.
It's all black, white and grey.
I am a diversity badass it seems.
Horses for courses. Do the query in whatever programming language, then just multiply the numbers together. I don't try to do left outer joins on my HP12-C calculator either.
Any other trading functions can be thought of as picking up alpha that other, less nimble, market participants are leaving on the table. That's the redistributionist part he's talking about there, but actually this is positive for society also because it increases liquidity also and makes the market more efficient. I also think that in general it's positive for society for the smartest and best people in a particular endeavour to be well-rewarded, because that gives a strong incentive to other smart people to step into the field.
Most of the carping about HFT comes from people who are losing business because they can't compete. Instead of moaning they should hire a roomful of brilliant programmers and write their own winning algos.
Now come to me when your credit union can give you a $50mm letter of credit to cover a shipment of goods from Brazil to China. In Portuguese and Mandarin, please, because the supplier and customer both want to see it. See, banks do all kinds of things that most people don't know or think about.
They get paid for doing something people want.
Three stooges of the high-frequency trading apocalypse
Secondly, regarding insight. This idea which everyone credits to Taleb is of course described all over the place. For example, as "the impossibility of inductive reasoning in the natural sciences" in The Mathematical Experience. As far as fat tails are concerned, every textbook on financial maths I own talks about fat tails the corrections that must be made to account for them, and they were all published before either of Taleb's books.