Quantum Qutrit-based Neural Networks achieved higher risk-adjusted returns than qubit-based models in stock prediction tests. Researchers compared these architectures against standard Artificial Neural Networks, finding all models exceeded 70% accuracy. The qutrit approach provides better consistency via the Information Coefficient. This suggests higher-dimensional quantum states improve stability in volatile financial forecasting.