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Predicting the Future of Finantial Markets with Machine Learning and Deep Learning
Explore machine learning models for financial market prediction, detailing data challenges, windowed forecasting architecture, and empirical results from two recent papers.
In this presentation, I will dissect the methodology and implementation behind the models used in my two recent papers:
• https://doi.org/10.48550/arXiv.2410.21291
• https://doi.org/10.1016/j.dajour.2025.100633
I will walk through the key challenges encountered—ranging from large-scale data acquisition and preprocessing to designing a robust windowed forecasting architecture for forward predictions. Finally, I will present the empirical results and discuss the broader implications of using AI models, such as LSTMs, to generate predictions of the future with a degree of certainty, and how it would impact the future of humanity.
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