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Sampling - Variational Auto Encoder - Ensemble: In the Quest of Explainable Artificial Intelligence
It is a hybrid architecture where VAE combined with ensemble stacking and SHapley Additive exPlanations are used for imbalanced classification.
Econometric Model Using Arbitrage Pricing Theory and Quantile Regression to Estimate the Risk Factors Driving Crude Oil Returns
The study highlights the impact of structural discontinuities on returns, which can be caused by changes in the global economy and the demand for crude oil. The inclusion of pandemic, geopolitical, and inflation-related explanatory variables add uniqueness to this study as it considers current global events that can affect crude oil returns. Findings show that the key factors that pose major risks to returns are industrial production, inflation, the global price of energy, the shape of the yield curve, and global economic policy uncertainty. This implies that while making investing decisions in WTI futures, investors should pay particular attention to these elements
