Project details

Short-term financial asset forecasting

Published by: Generali Assicurazioni

Status: CLOSED


Application domain: Finance

Budget (EUR): FROM 30000 TO 60000

Project description

In the context of the exchange rate market, given a cross-rate, we are interested in assessing what is the best method that can exploit the information brought by its own past plus a list of exogenous variables in the prediction of movement over two time horizon: daily and weekly. We have a particular interest to see if, among the methodologies, deep learning techniques perform in this area.

Project goal

The project goal is to assess what is the best methodology and the most promising exogenous variable to build a prediction model for asset pricing.

This project is for R&D purposes: the expectation is not for a perfected algorithm ready to go in a production environment, but to have an exploration of many methodologies (including deep learning) to understand which has the most potential.