I have nothing to add to the waterfall of comments on the current events which put the industry on the verge of collapse. I just can’t help but notice the striking similarities to the 2001 IT bubble. The technicalities are vastly different of course but here is the repeating scenario. The Wall Street arrives at some false and comletely unjustified risk-return assumptions about something – computer technology in 2001 and securitization of bad loans at present – and starts pumping obsene amounts of money into the idea. The law of supply and demand kicks in and everybody starts playing along. IT startups sprung up left and right back then and mortgage brokers set out to lure financially illiterate to unbelievably cheap loans now. Which brings up to the main subject of the recent posts in this blog.
I am talking about people going to professions for which they have neither aptitute nor skills. I already mentioned proliferation of java “developers” in 2001 and financial “mathematicians” in 2007 in this blog. Could it be that it was those people who caused the bubbles to burst? See, the programmer who has no clue about computer science can not deliver a software product of reasonable compexity. Just can’t. What happens? Eventually the startup begins to show signs of weakness, its stock plunges from $300 to $3, and the investors lose (huge) money. What about now? Could it be that the models developed by armies of clueless analysts underestimated the risks in the subprime loans? And the executives were too happy with the short-term bottom line in both cases?
I have recently had a questionable pleasure to observe analysts at two big financial services (the word “MBS” is somehow associated with both of them) companies in very different parts of the country (one of the firms is almost dead by now by the way). Those were supposed to be seasoned professionals – not some fresh graduates of 1-year “Master”’s program. The sight was sad to say the least. The mediocrity was flowrishing.
They say that the time of complex derivatives is over so the demand for finmath programs would inevitably fall. I would say it’s for the better. I wouldn’t admit to those programs anybody without graduate degree in applied math, statistics or physics in the first place. I would even say that the programs themselves are utterly wrong approach to the problem because what is really needed is degree in economics on top of degree in math/statistics/etc. That first degree would take care of the bigger part of the finmath programs automatically. Regrettably, this is not going to happen. Just like the standards for software developers were lowered during the IT bubble and never recovered, it looks like there is not much to expect in the area of financial math either.
But I digress. You know, I have been actually planning to write about the ultimate way to hire a junior analyst all along. At first I planned to have a post on technical questions. Of course you can have them calculate some tricky limit testing their knowledge of undergraduate analysis to the limit so to speak or you can give them an elegant problem to ponder but I don’t thik that is enough to assess sombody’s abilities for practical work.
In my opinion the best way to deal with candidates for a quantitative job is to give them homework (perhaps at the end of some short interview aimed to weed out grossly inadequate). The work may involve obtaining a data set, cleaning it, coming up with a model, implementing a model and analysing results. Or it can be analysis of several technical papers and implementing some ideas from them. Or coming up with ideas on some recent project that your team was working on. A few days later have them do a presentation of the results and go through detailed discusion on each and every point. That’s it. See, you don’t even have to come up with tricky brainteasers. If (s)he even shows up with the results – that alone tells a lot. The discussion would naturally highlight all the strengths and weaknesses of the person. Treat them as colleagues not enemies you have to defeat intelectually. You do not want to have enemies in the current market…
December 5, 2008 at 6:52 pm |
I like this homework approach. It tests how one would approach a new problem and think through it and take it to conclusion. Are you going to interview anyone anytime soon?
December 6, 2008 at 12:22 pm |
These days a few interviews I hear about are exit interviews
February 23, 2009 at 2:02 pm |
Why don’t you give us an example of this homework. then we can see if your approach actually works
April 26, 2009 at 6:24 am |
I like the homework approach very much. But you still have the risk that people get helped and that their solution doesn’t reflect their actual abilities.
By the way, if someone has a way to receive help from outside (s)he could be of some use though.
April 26, 2009 at 12:09 pm |
Well, maybe I was not very clear. See the presentation of the homework is not meant to be a soliloquy. Even the actual topic does not matter much as long as the solution has a potential of covering as many areas of expertise as possible. The point is the solution is supposed to be a subject of a conversation, the “conversation” being the most important part. If I ask somebody to come up with prepayment model for, say, certain type of MBS using historical performance and any market/economic factors of his/her choosing, I do not expect them to develop industrial strength model. But the moment I start going over a solution I can start asking questions on time series analysis, statistics, linear algebra, interest rate theory (if they use interest rate(s) as factor(s) – if not, then I can ask why), etc etc. So the homework is really a consistent way to test the depth of their knowledge and if they used the outside help, typically it is very easy to spot it right away.
May 19, 2009 at 4:12 pm |
You got it sport on.i intend to do a financial engineering honours degree .i have done a bsc maths degree and i strongly believe i am up to the challenge mathematically.at the moment teaching and frustrated.any advice .no experience in the industry .turning 34.south africa .