Best Degree at LSE for trading
Hi. I’m an incoming 1st year undergrad bsc math and econ. I’ve been looking into trading (both quant and discretionary), and it seems LSE isn’t as much of a target as other top unis. Was wondering if moving to the bsc math with data science or financial math and stats would be better, as I heard firms don’t like econ/finance grads because they come into the industry with false knowledge. The math with econ also looks good and I’ve been told by current students that moving between these is easy in the first year. Any thoughts?
Based on the most helpful WSO content, LSE is indeed a strong institution for finance-related careers, including trading, though it may not always be as highly targeted as Oxbridge or Imperial for certain quant-heavy roles. However, your choice of degree can significantly impact your prospects in trading, especially for quant roles.
Here’s a breakdown of your options:
BSc Mathematics with Data Science: This degree is highly relevant for quant trading roles, as it combines strong mathematical foundations with data science skills, which are increasingly in demand in trading firms, especially for algorithmic and high-frequency trading.
BSc Financial Mathematics and Statistics: This is another excellent choice for trading, particularly quant roles, as it focuses on the application of mathematics and statistics in finance. It aligns well with the technical skills sought by trading firms.
BSc Mathematics and Economics: While this is a solid degree, it may not be as specialized for quant trading as the other two. However, it still provides a strong foundation in mathematics and economics, which can be valuable for discretionary trading roles or hybrid quant-discretionary roles.
Key Considerations:
Final Advice:
If your primary interest is in quant trading, prioritize degrees with a strong emphasis on mathematics, statistics, and programming. Firms value candidates with technical expertise and problem-solving skills over those with purely theoretical finance knowledge. Additionally, consider building programming skills (e.g., Python, R, C++) and gaining exposure to probability and stochastic processes, as these are critical for trading roles.
Sources: Path to Quantitative Trader at Hedge Fund, Here are the Target Undergraduate Schools in Canada, Intro to Investment Banking, Trading from non-quantitative degree, https://www.wallstreetoasis.com/forum/school/complete-european-master-guide-for-stquant-position?customgpt=1
I’d do math Econ and just learn to code on the side, or through coursework in math which will naturally have coding. Data science degrees are buns imo. Similar with financial math, just do math and you’ll naturally learn to apply it to finance and you’ll know more than most—especially in stats which isn’t the most intuitive if you can’t see the big picture.
My worry is that I think the extra pure modules you'd do on math econ aren't that applicable to finance. I was advised against data science too so thats fine. But the financial maths covers all the main topics in maths like analysis, calculus, linear algebra. Do you think that doing like optimisation theory/differential equations is better than the pricing/hedging/optimisation module?
Interesting, honestly maybe the math finance is more of an applied maths degree, which is definitely more applicable to trading. Depends what kind of trading you want to do though. For most types yea financial maths probably way better. Unless you wanna trade FTRs or super exotic derivatives then yea maths physics better.
Straight BSc Econ at LSE is super hard to get into so always great (maybe not for prop/qt), financial maths and stats is really good and probs best for quant, Econometrics and Mathematical Economics has a great rep in tradfi but idk if quant firms care. Maths and econ also very strong. All these are sufficient for sell-side trading gigs, probably fin math + stats for imc/drw type places.
Really? I thought fin math sounded soft to people in quant (what I read online I don't really know). I heard EME is very difficult to move onto but would be great if I could.
Can switch between any degree in the math department after first year (make sure to double check this). More important than the degree to get trading/quant roles is how you perform at interview, arguably a very meritocratic process. So the degree should be a function of 1) Signal (any quantitative degree at lse should be fine especially if your rest of cv is targeted to what you are aiming for. 2) A degree which will give you enough leeway and work around so that you can spend your time practicing market making and green book questions. 2nd year (where you will be recruiting for summers), the maths degrees at lse are known to be difficult. 1st year is pretty easy across the maths courses so can score high here with not a lot of effort. Play to your strengths- if you’ve done coding before, and are good at it, choose maths w data science. If you’ve never coded before, don’t choose maths w data science as some exams are still in person coding and learning for these takes a lot of time. Final year offers a lot of flexibility for maths w Econ, and maths w data science, so can tailor it based on what you think is easiest to save time for recruiting if you need to. Note that FMS third year is pretty hard, a lot of modules such as measure theory, stochastic processes etc will take up a lot of time, albeit with a slightly easier second year than the other courses. Also important to know that out of your time at LSE, you do 18 half units, 2 of which are your first year average. You may not understand what I meant but essentially you need 10/18 half units at a certain level to get your degree grade. So if you do really well in second year, then your third year you can chill + recruit. Same way that if you do terribly in second year because you were focussed all year on recruiting, you can still get a first/2:1, if you do super well in your third year - again emphasising why I’m saying to take the course which has more optionality of modules for ease down the line. In summary, remember that most of what you will learn that is useful for your job will be learnt on job. You need to pick something that is a degree with good signal (anything quantitative at lse) which offers optionality down the line in terms of modules (ease + coursework based) such that you can, if need be, put your degree on the backfoot and recruiting first.
All current students I spoke to said its possible so hopefully can move if I need to. So basically, it sounds like I should just do the easiest one so I can grind the relevant stuff as the degree content probably wont be.
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