Advice from science graduates in a quant job

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SUMMARY

The discussion centers on the career path of transitioning from a physics undergraduate degree to quant jobs in finance. Key recommendations include focusing on programming skills, as they are critical for securing quant internships and succeeding in interviews, which often emphasize algorithmic problem-solving. Suggested courses include Mathematical Economics, Econometrics, Time Series Analysis, and Multivariate Economic Analysis, which can enhance quantitative skills. Participants agree that while finance knowledge is beneficial, strong mathematical and programming foundations are paramount for success in quant roles.

PREREQUISITES
  • Strong foundation in programming languages (e.g., Python, R)
  • Advanced knowledge of probability and statistics
  • Understanding of algorithms and data structures
  • Familiarity with quantitative finance concepts
NEXT STEPS
  • Research programming techniques for quantitative finance applications
  • Learn about financial modeling and risk management
  • Study advanced econometrics and time series analysis
  • Explore resources on algorithmic trading strategies
USEFUL FOR

This discussion is beneficial for physics undergraduates, aspiring quant analysts, and anyone interested in transitioning to finance from a STEM background, particularly those seeking to enhance their programming and quantitative skills.

cesaruelas
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I am doing a physics undergrad degree. I'm fairly settled now on applying for grad school in mathematical physics. Anyway, I want to have a fair amount of money to spare in my life and I'm considering quant jobs as a plausible career path for me. The question is should I use my spare credits in college on this courses (the books on which the courses are based in parenthesis):

- Mathematical economics (Mathematical economics by Takayama and Elements of dynamic optimization by Chiang)
- Econometrics I/II (Learning and practicing econometrics by Griffiths and Introductory Econometrics: A Modern Approach by Wooldridge)
- Time series (Applied time series modelling and forecasting by Harris, Time series analysis: with applications in R by Cryer, and Applied econometric time series by Enders)
- Multivariate economic analysis (Multivariate data analysis by Hair)

The pre-reqs are math courses which I have already taken so there is no problem with that. Would you have taken/did you take courses like these back in college? Should I just do a part time masters in financial mathematics while in grad school? Any useful advice you have for someone in my position?
 
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Do a search for Two-fish and see their posts.

My impression is that you'll need programming experience more than anythign else you listed. Also, keep in mind that career has changed considerably over the past three years.

See quantnet and wilmott forums for additional information.
 
I agree with Locrian. Get programming experience more than anything. I'm a PhD student in physics right now and recently acquired a quant internship for the summer. I had a very good contact at the company but the main reason that I was hired was because I'm handy with programming. The entire interview(s) were questions concerning algorithms and how I would solve certain problems through programming. There was some "finance" talk throughout the interviews but if I didn't know something I just asked for further explanation then proceeded.

For the record, I have never taken a finance class but I do know a little bit from reading about it occasionally. I would venture to guess that the reason they want math/physics/CS people is because they can handle complex math ideas. I'm not saying finance people can't but there's a reason that the quant jobs I've seen advertised don't ask for finance degrees.

Of course, make sure you know probability and statistics because anything computationally heavy will involve some form of those... Probably.
 

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