Sustainable finance: Prediction of returns and volatility through Machine Learning techniques.

Project: Research Project

Project Details

Description

The objective of this project, as part of the financial field, is to fundamentally study the dynamics of the prices of conventional and renewable energy assets through the prediction of their volatility and their returns.

For this, conventional econometric techniques and non-linear models known in the literature as Machine Learning models are used.

The foregoing is relevant within the literature as it contributes to the understanding of the operation of energy market prices and by presenting evidence of the performance of innovative forecasting techniques (Machine Learning) comparing them with traditional econometric techniques in the area of financial econometrics.

Commitments / Obligations

2 scientific articles.
StatusFinished
Effective start/end date6/1/2111/20/23

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities

Main Funding Source

  • Installed Capacity (Academic Unit)
  • Starter Funds

Location

  • Bogotá D.C.

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