Bayesian neural networks for better insight into markets
The complexity of financial data has rapidly expanded over the past two decades. This poses challenges for appropriate and effective tools for data analytics. Econometrics relies on parsimonious probabilistic models aimed at describing the economic phenomena. While it allows for models of great interpretability and excellent properties, it cannot upscale and embed the complexity of such modern data. Conversely, machine learning proved to be of high appeal for tackling a broad class of challenging multidimensional big-data problems. The EU-funded project BNNmetrics proposes to apply a class of ML methods known as Bayesian Neural Networks as a feasible tool for modern econometric research. This will significantly improve modelling processes, analyses and insights into the complexity of real markets.
Fields of science
Call for proposal
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