Suraj Kharal

Machine Learning Failures in Broker-Driven Emerging Markets: Concept Drift, Regime Switching, and Structural Breaks — Evidence from NEPSE Transaction-Level Data

2026 · Zenodo (CERN European Organization for Nuclear Research)

Machine learning models have demonstrated strong predictive performance on developed market data, yet theirapplicability to broker-driven emerging markets remains poorly understood. We evaluate 12 models across five architecturalfamilies — including XGBoost, LightGBM, CatBoost, LSTM, GRU, …