I am an enthusiastic and hard-working PhD student in statistics with a broad interest in the intersection between statistics/machine learning and finance/economics. I am seeking a challenging and research-driven environment where I can make a meaningful contribution.
Currently, I am a PhD student in Statistics at the London School of Economics, and funded by the Economic and Social Research Council. My main research interests revolve around Bayesian inference on state space models.
Before I joined LSE, I obtained a master's degree in Quantitative Finance from ETH Zurich and University of Zurich. I have work experience in asset management through the excellent portfolio management program (https://www.cpm.uzh.ch/en.html) during my master's studies, and from internships in the research and portfolio management division at Deutsche Bank/Deutsche Asset Management . A more detailed copy of my CV can be downloaded on my homepage (https://paschermayr.github.io/).
I am planning to highlight some of my projects and related topics that I am working on by gradually sharing blog posts here. Most of them will evolve around new concepts and theory. This gives me time to gather my thoughts and ideas, and you an introduction about topics that are typically taught in a more rigorous way.
So far, I have open sourced several software libraries on Markov Chain and Sequential Monte Carlo methods. For instance, Baytes.jl is a package to perform Bayesian inference. It consists of several sub-libraries, such as BaytesMCMC.jl], BaytesFilters.jl, BaytesPMCMC.jl and BaytesSMC.jl, and provides an interface to combine kernels from these packages. Moreover, I created a library to perform Automatic Differentiation on (nested) Model parameter structures, see ModelWrappers.jl. You can see a portfolio of my software contributions on my Github profile: https://github.com/paschermayr
If you are looking to collaborate on a research task, either in academia or in industry, do reach out. I am always happy to participate in interesting new projects!