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MSc in HPC and Big Data for quant finance role?


New Member
Hey! Apologies if I am posting at the wrong place but this is a thing that has been moving in my mind since a very long time. I am just completed my bachelors in theoretical physics and now I have to choose a masters program out of these two:

1. MSc in Data Science (Machine Learning and Artificial Intelligence track)
2. MSc in HPC and Big Data

There are several research directions in MSc in HPC and Big Data such as:

  • Mathematical and Supercomputer Modeling
  • Big Data and distributed deep learning
  • Modern Computing architectures and technologies
  • Efficient Numerical Algorithms
  • Computational Complex Systems
For a future quant finance role, I am looking at Big Data and distributed deep learning and efficient numerical algorithms. Also, I found an interesting research topic in one of the labs i.e. Risk Modelling and high dimensional integrals. The problem description is as following: Many stock prices can modelled using Brownian motion, i.e. the next state depends on the previous state plus some random event. Important statistical options (for example, option calls) can be then estimated as expectations of random process. The straightforward way is to do Monte-Carlo simulation, but it can not give high accuracy. Another way is to write down the expectation as a path integral and then approximate it by a multi-dimensional integral. For similar integrals we have recently developed a new technique, [1504.06149] A low-rank approach to the computation of path integrals. The idea is to test it for examples from risk analysis.

What do you think guys? Will it be the right step given the fact that I want to take up a quant trader/quant finance job in future?

or should I go with the more conventional MSc in Data Science - Artificial Intelligence and Machine Learning?