Leveraging momentum clustering and PID control for enhanced portfolio management

Efficient wealth management in dynamic financial environments is crucial for maximizing returns and mitigating risk. Therefore, this study presents an adaptive portfolio management strategy that combines momentum-based clustering, a Proportional-Integration-Derivative (PID) controller, and efficient frontier (EF) analysis to construct optimal portfolios in dynamic financial environments. A novel integration of a PID controller dynamically adjusts the asset weights to address the limitations of static optimization methods. EF analysis is then employed to identify portfolios with optimal risk-return trade-offs. Our dynamic strategy demonstrates competitive performance compared to conventional benchmarks. From 2017 to 2023, the approach yielded a cumulative return of 135.5%, surpassing Standard and Poor’s 500 (46.66%), Russell’s 2000 Index (11.47%) and NASDAQ (67.88%). These findings suggest that the integration of clustering techniques and PID controllers offers a promising approach for portfolio management.