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A few noob questions

domeface said:
Pardon my ignorance, but I was still learning to count in 2000; what was significant about e-commerce programs then?
Click to expand...

They were the hot thing at the time -- lots of e-commerce programs were being offered with unis falling over themselves to introduce them. The leading MBA programs had e-commerce courses which were heavily subscribed to (often even the MBA could be tailored to an e-commerce concentration). Then the dotcom bubble exploded towards the end of 2000. That isn't to say web development and e-commerce ceased -- quite the contrary -- but the gloss had left, the insane valuations and the crazy dreams had gone. These days web development people are a dime a dozen.
 
I've ordered a copy of The Complete Guide to Capital Markets for Quantitative Professionals as recommended by atreides, and I'm hoping to gain some insight into general finance stuff with this.

While waiting for the book to arrive I've started looking a bit more into different sorts of quantitative roles, and I have a few questions:


In "derivatives pricing", am I correct in thinking that the job is to analyse the statistical data for the appropriate market/commodity/whatever to attempt to determine the best price at which to buy/sell the given product? (eg if it was a product based on oil, my job would be to examine past trends and statistics of oil prices so I can figure out what they're likely to do in the future (this is where the maths would come in I assume?) then price the product accordingly).
If I'm (roughly) correct in my analysis, to what degree is this process automated by models etc? Because to use the previous example, I would assume that with something as common as oil, surely a model would already exist that could automatically predict the price at least as well as any individual analyst? So outside of the need to price the occasional very exotic product, what is the need for a highly-trained mathematician over a glorified secretary to input numbers into a model and use the output?

Furthermore, I've recently discovered the existance of 'algorithmic trading', which is described by Max Dama as 'programming computers to trade'; my only question with regards to this is, is this role as mathematical as the likes of derivatives pricing et al, or is it more of a purely programming role? If the former, is the math used similar to that of (my interpretation of) derivatives pricing, (ie using statistical data to predict market shifts, which can then used to gain profit by buying/selling the appropriate assets), or is it different in some way?
And regardless of math content, why is it not the case that after a program has been built, it can just be left to run indefinitely? Obviously any drastic market shifts may require alterations, but surely the whole purpose of such a model would be to adapt to and take advantage of general fluctuations in the market?

Finally, what exactly does a 'desk quant' do - Mark Joshi's guide says they 'implement pricing models used by traders', but what is meant by 'implementing' them? I'm slightly confused about this.

If all of this information is already explained in some easily accessible guide or something that I've missed then I'm very sorry and would appreciate being directed to it, otherwise answers to these questions would be very helpful.

Thanks
 
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