Roland studied Maths at Oxford, Cambridge and Imperial. He worked in the financial industry as a quantitative developer building models for interest rates exotic derivatives and optimization algorithms for initial margins. His research interests lie in Mathematical Physics, Monte-Carlo Methods and Non-linear Programming.
Differentiable programming for particle physics simulations
We describe how to apply adjoint sensitivity methods to backward Monte-Carlo schemes arising from simulations of particles passing through matter. Relying on this, we demonstrate derivative based techniques for solving inverse problems for such systems without approximations to underlying transport dynamics. We are implementing those algorithms for various scenarios within a general purpose differentiable programming C++17 library NOA
Are Cryptocurrency Markets Running Behind the Fed? A Significant Shift in Crypto Markets Microstructure
Roland Grinis, Andrei Kislitsyn, Ilia Drozdov, Konstantin Shulga
In this research we show that 2021 became a year when crypto markets significantly adjusted behavioural patterns, showing an increased institutional influence.
We have come to two key conclusions that might indicate significant changes in the cryptocurrency market microstructure.
Firstly, in contrast to recent research, we note that BTC/USD was sensitive to major Fed policy announcements in Q2-Q3 2021 similar to main asset classes.
Secondly, OTC Liquidity Providers tend to provide twice as narrow spreads in comparison to Centralised Crypto Exchanges during market volatility related to macroeconomic news.