In the Barcelona Quant Challenge, my team and I engaged in a quantitative finance project focused on developing and testing a pair trading strategy. We applied advanced statistical methods, including the Augmented Dickey–Fuller (ADF) test, to assess the stationarity of asset pairs. This was essential in identifying pairs that had a stable, long-term mean-reverting relationship, which formed the basis for our trading signals. We further employed Ordinary Least Squares (OLS) regression to refine our pairs' selection and improve the robustness of the strategy.

To validate our approach, we implemented a backtesting strategy that simulated trades over historical data, allowing us to evaluate the performance of our pair trading model under different market conditions. Throughout the challenge, we had the opportunity to listen to insights from industry recruiters and experienced quants, who provided invaluable feedback and shared practical knowledge on trading methodologies. This project gave us firsthand experience in applying quantitative techniques to finance and deepened our understanding of data-driven trading strategies.

Thanks to G - Research for selecting me for the opportunity!

G - Research Official Site