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Question on courses for Risk, Portfolio or Hedging

Joined
12/9/12
Messages
21
Points
11
Hi all,

I have a quick question. Is taking courses on advanced derivative pricing using stochastic calculus, volatility smile, numerical PDE and Monte Carlo useful for jobs in Risks or Portfolio Manager?

(My education will consist of a lot of statistics, programming, and optimization)

I am interested in jobs that involve hedging and analyzing risk in investment.

Thanks
 
Definitely, all these are needed for quant jobs nowadays.
 
Why don't you ask what is useful rather than if certain courses are? I think Ken Abbott will tell you that regarding risk Time Series is especially useful.
 
Why don't you ask what is useful rather than if certain courses are? I think Ken Abbott will tell you that regarding risk Time Series is especially useful.

Because my schedule already have a lot of statistics and optimization which are useful for portfolio management (all are in PhD and master's level). I am considering to include additional derivatives-pricing-related courses but hesitate about it.
 
Hi all,

I have a quick question. Is taking courses on advanced derivative pricing using stochastic calculus, volatility smile, numerical PDE and Monte Carlo useful for jobs in Risks or Portfolio Manager?

(My education will consist of a lot of statistics, programming, and optimization)

I am interested in jobs that involve hedging and analyzing risk in investment.

Thanks
I can only speak to Risk.
If you're doing model review, you need to know stochastic calc and PDEs. For desk coverage, statistics (especially TS, multivariate) is helpful. For risk modeling, stat and Monte Carlo. SQL is helpful for all.

The challenge is that classroom knowledge of many of these topics, when taught in an academic vacuum, won't give you what you need. The real-world problems associated with finance applications don't necessarily involve getting the core calculation right, per se, al though that's certainly important. The challenge is identifying all of the things that can mess up. These include position aggregation issues (especially proof and control), time series noise (missing data, et. al.), and ensuring that you are meeting reg requirements. Unfortunately, few academics (and none who don't have practical experience) can teach this. The pure math and statistics in risk could easily be taught by a 27-year-old newly-minted Ph. D. The actual application is much, much trickier.
 
Depends what product you work on. If you are covering cash products then even elementary math and some knowledge of time series can be sufficient. It's the non linear products where financial engineering gets fun. So if you cover options etc it is usefull to know a little bit of stoch calc and volatility smile. I have yet to see any PDE being used on a job in trading or risk. If you are a desk quant than its important. Stoch calc is useful because if you are doing swaptions, you need to understand SABR model very well so it comes in handy although the best swaptions trader I know is just an undergrad in business and he is one of the top swaption traders on the street and is far from a quant but knows SABR like the back of his hand.

So to get an entry level job definitely useful to know all of the above as your competition most likely will as that is the standard now but the usage of the knowledge really depends on the products/function you work in.
 
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