Research & Statistics

How do we excel at what we do? Naturally, we are in a constant state of learning.

A big part of our work is to test and evaluate new approaches and technologies.
One of these technologies, though being around for quite some time, is getting more and more attention recently — that is Machine Learning. We have acquired extensive knowledge on using Machine Learning for the FinTech sector. Be it training an AI to choose the optimal allocation
in a financial portfolio via Reinforcement learning or utilizing deep networks to perform
a sentiment analysis of Social Media data, we know how to handle it.

Additionally, we conduct our very own fundamental research and perform quantitative analysis to figure out which crypto projects are worth investing in. Yet the persisting question is:
how much should we invest in each asset? We get the answer to this question through research in the field of financial mathematics, in particular in the field of portfolio theory. This allows us to create a portfolio that gives us the best possible risk/reward ratio.

Other points of our interest in mathematical finance include Monte-Carlo simulations
for Backtesting of trading strategies and deploying stochastic optimization methods
in High-Frequency-trading.