[bmqib]

And why isn't algo trading more popular?

[President_Ben]

No. But it really helps to get you going.

Limited alpha and the landscape shifts very quickly. Work done six months ago can be worthless. Consistent edge is rarely found.

[SonnyZH]

I'd say it's a 'requirement' seeing almost every other applicant will have a PhD in Maths/Physics/etc. especially if you're degree isn't very quantitative.

[Regent]

(Original post by SonnyZH)
I'd say it's a 'requirement' seeing almost every other applicant will have a PhD in Maths/Physics/etc. especially if you're degree isn't very quantitative.

But if you're degree isn't very quantitative what chance do you have of doing a PhD in Maths? Think about it.

[Hackett]

funnily enough - I know a recent grad who is in Algo trading at a BB who did politics at a non - target.

[SonnyZH]

(Original post by Regent)
But if you're degree isn't very quantitative what chance do you have of doing a PhD in Maths? Think about it.

What I meant by not very quantitative was something like Economics, with respect to Maths for example its substantially less quantitative.

(Original post by Hackett)
funnily enough - I know a recent grad who is in Algo trading at a BB who did politics at a non - target.

I'm sure there are exceptions but I'm sure he had a very solid numerical/computing background. I mean, if you're going to be using software programs and spreadsheets to track patterns in security prices/volumes/frequency at which they are traded; relying heavily on mathematical formulas, I assume you'll need to know maths.

[poohat]

often yes if youre doing the actual algorithm design, but depending on circumstances and background a Masters might be enough

algo trading also requires a lot of support staff so if you have a programming background then you might be able to find employment designing the software and trading systems. Also for more senior (managerial) roles rather than the technical staff, you might find experienced people with professional degrees like a CFA, or just really experienced traders of no particular academic background.

(Original post by bmqib)
And why isn't algo trading more popular?

its huge

[Oorlog]

A MFE from a top school would probably do as well.

[enlim]

(Original post by Oorlog)
A MFE from a top school would probably do as well.

What about LSE's financial mathematics msc?

The hardcore MFE's seem to be in the states.

[SonnyZH]

(Original post by enlim)
What about LSE's financial mathematics msc?

The hardcore MFE's seem to be in the states.

It would be very hard for anyone with only a Masters to surpass a PhD in the research area. These are usually specialized individuals in Physics/Mathematics who come up with ideas and then research and develop algorithms based on these ideas. These algorithms are then backtested by the research team and tweaked and send to the Quant Developers, at least it's usually how it works in hedge funds.

[lol_wut]

(Original post by Oorlog)
A MFE from a top school would probably do as well.

I thought MFEs focus on training people for derivative pricing roles, so probably not the best degree for this sort of area.

[Oorlog]

(Original post by enlim)
What about LSE's financial mathematics msc?

The hardcore MFE's seem to be in the states.

I don't have any hard data to back up my claims but from what I've seen when it comes to placement reports, quant networks etc US schools seem to outclass UK ones by miles. Elite schools like Stanford and Princeton have wicked placement records (i.e. 99% ends up working for top-tier HF's or banks like GS, MS, JPMorgan etc.). Then again, selectivity rates range from 3-14% for top programmes, so competition is fierce.

-----------

Don't forget, a MFE is a 1 or 2-year stint during which you spend 100% of your time developing quant skills. While a PhD may be 3-4 years a LOT of that time is NOT spent on developing quant/research skills.

[Zalachenko]

From what I learned from them, this is how algorithmic trading works at hedge funds (or any place basically).

You have PhD strategists/researchers who usually have degrees in physics/mathematics/computer science who come up with ideas and then research and develop algorithms based on these ideas. The algorithms are then backtested by the research team sent to the developers.

The quant developers (expert programmers) are the ones who implement these algorithms and then optimize the code to the best of their abilities. The algorithms have to be interfaced on some platform (TT usually) and the programmers take care of this part.

Then come the "traders" who work on asset allocation and execute these algorithms onto the market at specific times depending on the parameters stated in the algorithm in terms of volatility and so on. Most algorithms I have seen are market neutral so the trader's job is to just launch the algorithms onto the market when they open and then sort of "baby sit" or allocate asset to it accordingly in a risk management framework. Many a times it is a circular process. The traders since they are locked into the markets, will come up with ideas on trading and will talk with the PhD strategists who will refine and turn the idea into an algorithm, and the process starts again. From the few funds I interviewed at and got offers from it seems like the smallest number of algorithms (robots) a fund has run is around 800 so everyone is usually pretty busy. I recently saw one trader launch/manage/monitor more than 100 algorithms in the european markets.

There ARE exceptions to what I stated. I am just speaking from experience. I was working with a hedge fund last semester where it was just a trader/quant developer who were doing the algorithm trading. The trader came up with ideas and concepts and the quant developer would implement them. I have also met people who do ALL three at hedge funds (Silos) and they have had PhD's in EE/Math from MIT/Berkeley and other ivies/target schools. The triple hitters are almost always people who have done significant math and programming for a minimum of 5-10 years.