I am PhD student at the University of Neuchâtel, with a focus on financial markets. Specifically, I study how microstructure variables impact asset prices and participate in price formation. In my working paper, I propose a theory where prices are formed in a purely mechanical manner through trading and derive testable predictions about trading volume, price impact, trading frequency, bid-ask spreads, order imbalance, market depth, and volatility.
I am also passionate about interdisciplinary projects and computational methods. In particular, I am the developer of COVID-19 Data Hub (Scientific Data), I have authored a classification algorithm inspired by Born’s rule (NeurIPS), and I maintain several R and Python packages including a package for high dimensional numerical and symbolic calculus in R (JSS). For my contributions, I have received grants and awards from IVADO, the R Consortium, and Google Cloud.
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