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Which specific math PhD research area is the best to be a quant

Which specific math PhD research area is the best to be a quant

  • Stochastic Analysis (Levy Process, Rough Path Theory)

    Votes: 1 11.1%

  • Stochastic Analysis (Backward Stochastic Differential Equation)

    Votes: 1 11.1%

  • Numerical Methods (Monte Carlo, Finite Difference)

    Votes: 5 55.6%

  • Stochastic Modelling (for example: Interest rates modelling)

    Votes: 2 22.2%

  • Behavioural Finance

    Votes: 1 11.1%

  • Stochastic Control (for example: utility difference)

    Votes: 0 0.0%

  • Stochastic Control (Dynamic Programming, HJB, Maximum Principle)

    Votes: 1 11.1%

  • Portforlio Selection (apply Stochastic Control)

    Votes: 1 11.1%

  • Financial Time Series

    Votes: 2 22.2%

  • Robust Hedging

    Votes: 1 11.1%
  • Total voters
    9
  • Poll closed .

Jones Ad

Joined
3/8/13
Messages
5
Points
11
To study a Math PhD is one of the best ways to become a hard-core quant. But which research area is the best, especially for hard-core quants? The perfect situation is that the papers PhD students are reading for PhD thesis are also read every day by quants.

Please leave your comments. Many thanks.
 
Jones Ad said:
Any suggestions？
Click to expand...

I think numerical methods are increasingly important as well. Machine learning could also be useful and that is a topic I hope to research myself for my Stats PhD starting this fall...

Are you already in a PhD program? If so, where?
 
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