Best Degree for trading

Between these, which undergrad degree is seen in the best light for trading.
Imperial: Math with Stats
LSE: Financial Math and Stats or Maths and Economics
UCL: Math and Economics

From reading, it appears trading is less like IB where uni name is all you need. It also seems like the emphasis on maths is alot higher despite most the calculations being mental arithmetic so not sure which of these is better. I'm aware theres more to skills than just a degree, but you can always work on skills unlike choosing a degree.
And, I get imperial is most target for quant trading but would any of the others rule out that career path?

14 Comments
 

When it comes to trading, especially quant trading, the degree you choose can play a significant role in shaping your career path. Based on the most helpful WSO content, here's how these degrees stack up:

  1. Imperial: Math with Stats

    • This is the strongest option for quant trading. Imperial is highly regarded for its technical rigor, and a Math with Stats degree aligns well with the quantitative demands of trading. The focus on statistics is particularly valuable for roles involving data analysis, probability, and stochastic processes, which are core to many trading strategies. Imperial's reputation as a target school for quant trading further boosts your chances.
  2. LSE: Financial Math and Stats or Maths and Economics

    • LSE is a strong name, especially for finance-related roles, but it is slightly less technical compared to Imperial. The Financial Math and Stats degree is a solid choice if you want a balance between finance and quantitative skills. However, Maths and Economics might lean more towards traditional finance roles rather than hardcore quant trading. That said, LSE's brand name and alumni network in finance are excellent, so it won't rule out a trading career.
  3. UCL: Math and Economics

    • UCL is a respected institution, and this degree offers a good mix of quantitative and economic theory. However, it is slightly less specialized for quant trading compared to Imperial's Math with Stats. While it won't rule out a trading career, you may need to supplement your education with additional technical skills (e.g., programming in Python or C++, machine learning, or stochastic calculus).

Key Takeaways:

  • Imperial: Math with Stats is the best choice for quant trading due to its technical focus and strong reputation in the field.
  • LSE: Financial Math and Stats is a close second, especially if you want a mix of finance and quantitative skills.
  • UCL: Math and Economics is a solid option but may require extra effort to build the technical skills needed for quant trading.

Additional Advice:

  • Regardless of your degree, focus on developing programming skills (Python, C++), mental math, and a strong understanding of probability and statistics. These are critical for trading roles.
  • Participate in trading competitions, internships, or platforms like Quantopian to demonstrate your ability to find alpha and apply quantitative methods.
  • Networking is key. Leverage alumni connections from your university to break into trading roles.

In short, none of these degrees will "rule out" a trading career, but Imperial's Math with Stats gives you the best edge for quant trading.

Sources: Best internships for Quant Trading?, How to be a Millionaire Trader, Deciding on quantitive majors/career path?

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 

So, 2 big reasons why math is emphasized. 1, most of the trading nowadays is done through models. Having some mathematical understanding means you understand generally when the output of a model is fishy. It also gives you the basic ability to make basic models(or more realistically make crappy ones and have the strats fix them). Other reason is just that math and STEM generally is harder, and as a result you often build up better problem solving skills. Those skills come in handy when you're trying to work on really tricky problems in trading. Mathematical intuition is something that can be taught, but only through doing a lot of math. 

 

Math stats is what I did, but math econ is also decent. Both will serve you well. The problem is that degree names don't always stack up. I would look at what the programs actually teach you past the names. Time series, regression analysis, some ML, predictive modeling, causal inference, game theory, and econometrics are all classes I would suggest taking. 

 

Fair enough!
I do hear some people say the more stem the better and thus places like imperial is better. Do you thinks it’s true, insignificant/marginal or false? And if you’re at lse, do you think the econ name helps in stuff like trading or is financial math and stats more attractive in the field?

 

Why? Ive (naturally) heard both answers of LSE/Imperial but is the reason purely mathematical content? Because I've looked into contents/notes at both universities and the main difference I see is Imperial's applied maths is more on the mechanical side whilst LSE is of course econ/finance focused?

 

Prospect in S&T - Equities

Why? Ive (naturally) heard both answers of LSE/Imperial but is the reason purely mathematical content? Because I've looked into contents/notes at both universities and the main difference I see is Imperial's applied maths is more on the mechanical side whilst LSE is of course econ/finance focused?

In terms of content, I can't answer. 

In terms of volume of people who end up in quant / trading markets, Imperial has got a lot more people and way more firms recruit from Imperial. 

LSE to me is more of an M&A culture-specific university which isn't to say that they don't get trading offers but just that I see it less. 

 

I got to LSE in department of maths - pick Imperial!

Only downside is the social scene (less girls).

 

May I ask why’s specifically? I prefer imperial anyways but what makes you say it as if lse is significantly behind (as you an lse student)

 

Aspernatur et sint praesentium aut et enim cumque nobis. Perferendis qui nobis quo.

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