Deep learning, Fairness, Stock market forecasting, LSTM, AI ethics, Bias mitigation, Interpretability, Statistical fairness evaluation, Error parity, Calibration curves, Transparency, Responsible AI,
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Enhancing Fairness and Transparency in Deep Learning- Based Stock Market Forecasting
Abstract: Over the past few years, Deep Learning Models have gained prominence as a very effective means of predicting future financial markets because these types of models are capable of identifying and modelling complex non-linear data relationships that may otherwise be missed by human analysts. By analyzing huge amounts (millions of observations) of historic data about the market, the technical indicators and sentiment derived from news articles, social media or analyst …
Published in NOLEGEIN Journal of Financial Planning And Management · Vol. 9, Issue 1, 2026 Read article