Members: Harrison Bernstein, Rachel Kahn, Richard Zhao, Felipe Quiroz, Adam Coussin, Luke Currier
As part of a collaboration with UTS, we aim to research, train, and build a machine learning model with the goal of predicting traders' profitability.
We conduct a literature review to identify potential factors influencing traders’ profit and loss (PNL) in finance trading, particularly in forex trading, and construct a conceptual model to describe them.
Using forex transaction data provided by UTS, we explore the correlations between various factors and PNL.
We build a data-driven prediction model to predict the profitability of traders by taking various factors as input. This model will offer brokers valuable insights into optimizing risk management strategies.