Myles Sjogren
Mathematical Finance
Cohort 2020
University of Calgary
Mathematical Finance
Cohort 2020
University of Calgary
Mathematical Finance
University of Calgary
Master's
In 2019 I completed a Bsc(Hons) in applied mathematics with a concentration in mathematical finance and risk management as well as a minor in statistics, I then started a Msc in financial mathematics in 2020.
I'm currently a thesis-based masters student at the University of Calgary in financial mathematics and was part of the NSERC-Create program in financial machine learning. Throughout my graduate studies I have focused my research on the practical applications of stochastic modelling and machine learning to financial markets. In particular, I have been working with high-frequency financial data to generate future price predictions and output real-time tradable signals through various means.
Futures First Internship Project Overview and General Compound Hawkes Processes for Mid-Price Prediction
This presentation summarizes the results of a sub-project of my internship focused on the stochastic modelling of historical limit orber book data. The purpose of this sub-project was to assess the existing theory surrounding and test the predictability of a well-established stochastic model, namely, the General Compound Hawkes Process. To this end, a new back-testing system was created to process data, fit all the proposed variations of the model, and generate predictions using different methods.
