Innovating Works

BNNmetrics

Financiado
Bayesian Neural Networks for Bridging the Gap Between Machine Learning and Econo...
The complexity and volume of financial data in modern financial markets have been exponentially growing during the last decades. Machine learning (ML) methods such as Deep learning (DL) have been widely utilized for several classi... The complexity and volume of financial data in modern financial markets have been exponentially growing during the last decades. Machine learning (ML) methods such as Deep learning (DL) have been widely utilized for several classification and prediction problems, given their intrinsic flexibility, appropriateness for large multidimensional problems, and ability to discover and adapt to non-linear patterns. However, the enormous number of parameters, their difficult interpretation and inability do deal with uncertainties represent DL’s main shortcomings. On the other hand, classic econometrics methods, of limited variables, great interpretability and with excellent probabilistic properties, have failed to prove appropriate for the analysis of modern high-frequency data. The application in financial econometrics of a DL sub-class of algorithms known as Bayesian neural networks (BNNs) is expected to revolutionize the process of modeling, analyzing, and understanding trading behavior in real markets. BNNs’ attractive properties have the potential of bridging the gap between classic econometrics and ML. This research will show measurable improvements over the current state of the art, both from the financial econometrics and the ML sides, in three problems defined on high-frequency financial data: volatility modeling, stock mid-price movement prediction, and interdependence analysis between stock prices. ver más
30/09/2022
AU
207K€
Duración del proyecto: 30 meses Fecha Inicio: 2020-03-25
Fecha Fin: 2022-09-30

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2022-09-30
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
MSCA-IF-2019: Individual Fellowships
Cerrada hace 5 años
Presupuesto El presupuesto total del proyecto asciende a 207K€
Líder del proyecto
AARHUS UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5