Quantum Qutrit-based Neural Networks achieved higher risk-adjusted returns than standard ANNs in stock prediction tests. Researchers compared QQBNs and QQTNs, finding that qutrit-based architectures provide superior consistency via the Information Coefficient. All tested models maintained accuracies above 70%. This suggests a niche performance gain for quantum-inspired models in high-volatility financial forecasting.