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  • Zürich, Switzerland

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JurajZelman/README.md
# About me

class QuantitativeResearcher:
    def __init__(self):
        self.name = "Juraj Zelman"
        self.role = "Quantitative Researcher"
        self.uni = "ETH Zürich & UZH, Charles University"

    def get_interests(self):
        self.finance = "Alpha Research, Portfolio Optimization, Market Making"
        self.comp_science = "Statistical Learning, (Deep) Reinforcement Learning"
        self.math = "Statistics, Math. Finance, Numerical Methods, Optimal Control"
        return f"{finance} and {comp_science} and {math}"

    def say_hi(self):
        print("Thanks for stopping by, hope you find some of my (public) work interesting!")


me = QuantitativeResearcher()
me.say_hi()

Technologies & Tools

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  1. airl-market-making airl-market-making Public

    The official repository for the paper Adversarial Inverse Reinforcement Learning for Market Making (2024) published and presented at the ICAIF'24 conference.

    Jupyter Notebook 36 2

  2. distortion-risk-measures distortion-risk-measures Public

    BSc thesis focused on distortion risk measures and reward-risk ratios.

    Jupyter Notebook 2

  3. multi-armed-bandits multi-armed-bandits Public

    Several multi-armed bandit strategies with additional holding option for smoother exploration.

    Jupyter Notebook 2

  4. siamese-neural-net siamese-neural-net Public

    Siamese neural network based on a pre-trained ResNet-18 convolutional neural network for image comparison.

    Python 5 2

  5. py-parallelization py-parallelization Public

    Template for parallelizing tasks in Python with the multiprocessing module.

    Python

  6. deep-hedging deep-hedging Public

    Jupyter Notebook 2 2