6 papers
Does the AI Productivity Dividend Diminish? Does the AI Productivity Dividend Diminish? A Validated Framework for Identifying the Shape of Firm-Level Returns to Artificial Intelligence
Louis Agyekum
Forecasts of the productivity dividend from artificial intelligence (AI) differ by an order of magnitude, partly because they extrapolate average gains observed among early, highly…
Forecasting in the Fog: Real-Time versus Revised-Data Evidence on Machine Learning's Edge over the Phillips Curve
Louis Agyekum, Obed Obese
ML inflation forecasts are almost universally trained on fully revised data, even though real-time forecasters never have such data, and reported feature importances are typically…
Bankruptcy Prediction via Hybrid Resampling and Stacking Ensemble Techniques with Explainable Artificial Intelligence (XAI)-Driven Analysis
Obu-Amoah Ampomah, Edmund Fosu Agyemang, Kofi Acheampong +3
This study develops and evaluates a bankruptcy prediction framework that integrates consensus-based feature selection, hybrid resampling, stacking ensembles, and explainable artifi…
Forecasting and Explaining the Phillips Curve: A SHAP-Based Comparison of Machine Learning and Traditional Time-Series Models for Canadian Unemployment and Inflation
Louis Agyekum
This study evaluates the out-of-sample forecasting ability of six model types: ARIMA, VAR, Random Forest, XGBoost, LSTM, and GRU, for monthly Canadian inflation from January 2012 t…
Machine Learning and the Random Walk Puzzle: Forecasting the CAD/USD Exchange Rate with Expanding Window Evaluation and SHAP Interpretability
Louis Agyekum, Edmund Fosu Agyemang, Obu-Amoah Ampomah +6
This study examines whether machine learning (ML) models can outperform the naive random walk benchmark in forecasting the monthly USD/CAD exchange rate. Using daily data from the…
Enhancing Credit Default Prediction Using Boruta Feature Selection and DBSCAN Algorithm with Different Resampling Techniques
Obu-Amoah Ampomah, Edmund Agyemang, Kofi Acheampong +1
This study examines credit default prediction by comparing three techniques, namely SMOTE, SMOTE-Tomek, and ADASYN, that are commonly used to address the class imbalance problem in…