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This study applies Modern Portfolio Theory (MPT) to optimize hotel demand forecasting by treating individual forecasting models as risk-bearing assets, aiming to minimize overall forecast error variance. The research demonstrates that MPT-weighted ensembles significantly outperform traditional models and equal-weighted combinations, achieving MAPE values below 5.1% and reducing forecast errors by over 80%. This innovative approach provides a systematic framework for balancing forecast accuracy and volatilit

Author
sophiedang.me
Language
EN