# About me
class QuantitativeDeveloper:
def __init__(self):
self.name = "Juraj Zelman"
self.role = "Quantitative Developer & Quantitative Finance Student"
self.uni = "ETH Zürich & UZH"
def get_interests(self):
self.math = "Math. Finance, Statistics, Numerical Methods, Optimal Control"
self.comp_science = "Statistical Learning, (Deep) Reinforcement Learning"
self.finance = "Statistical Arbitrage, Market Making, Portfolio Optimization"
return f"{self.math} and {self.comp_science} and {self.finance}"
def say_hi(self):
print("Thanks for stopping by, hope you find some of my work interesting!")
me = QuantitativeDeveloper()
me.say_hi()
- Zürich, Switzerland
Highlights
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airl-market-making
airl-market-making PublicCodes for my master thesis from ETH Zürich & UZH on reinforcement learning for market making.
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distortion-risk-measures
distortion-risk-measures PublicBSc thesis focused on distortion risk measures and reward-risk ratios.
Jupyter Notebook 1
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volatility-path-dependent
volatility-path-dependent PublicCode for the paper "Volatility is (mostly) path-dependent - Guyon, Lekeufack (2022)".
Jupyter Notebook 2
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multi-armed-bandits
multi-armed-bandits PublicSeveral multi-armed bandit strategies with additional holding option for smoother exploration.
Jupyter Notebook 1
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siamese-neural-net
siamese-neural-net PublicSiamese neural network based on a pre-trained ResNet-18 convolutional neural network for image comparison.
Python
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