Transforming portfolio optimisation: a hybrid machine learning and Monte Carlo approach for superior asset allocation

Puntos clave

• The aim is to enhance asset allocation strategies using hybrid machine learning techniques and Monte Carlo simulations.
• Develop a hybrid model combining machine learning methods with Monte Carlo simulations
• Test the model on various asset classes
• Evaluate performance compared to traditional strategies
• The hybrid approach achieved better asset allocation results than traditional methods
• Significant improvement in risk-adjusted returns
• The model demonstrates faster convergence in optimization compared to standalone methods

Resumen