Lithika Ranepura

Lithika Ranepura

Wealth of expertise in investment forecasting, having earned his MSc in Investments from the University of Birmingham. His dissertation, "An Interpretable WTI Crude Oil Prices Forecasting Model Using a Novel Hybrid Model," delved into the complexities of crude oil price fluctuations and proposed a groundbreaking hybrid model, the 3ANNLSTM. This model uniquely combines Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) networks, outperforming traditional statistical and econometric models by significant margins (71%-78.79%) in forecasting accuracy. By integrating explainability tools such as SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-Agnostic Explanations), Lithikaโ€™s model improved the transparency of complex machine-learning predictions, making it a valuable resource for industry stakeholders.

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