Joel Erickson is a recent graduate of UCO with a computer science major. During his undergraduate studies, Joel became interested in applying his computer science knowledge to financial trading. He created a trading infrastructure on his own, which incorporated a number of algorithmic and parameterized trading strategies.
In the summer and fall 2019 semesters, Joel started a project that used machine learning (ML) techniques to enhance trading strategies, with Dr. Gang Qian serving as his advisor. In the research project, Joel compared the effectiveness of various features derived from the price series of trading. His system also considered the uniqueness of financial data, which have distinctive characteristics such as time-dependencies compared to those of a typical machine learning application.
The result of his research showed that, by appropriately incorporating ML techniques, it was possible for a computerized trading system to maintain consistent profitability even in a declining market. The research also shows that the application of ML algorithms and techniques to financial trading is a promising direction in ML research due to its uniqueness. His results were presented as a research poster at the 2019 Oklahoma Research Day.