Combining Machine Learning and Agent Based Modeling for Gold Price Prediction

• Published in: Artificial Life and Evolutionary Computation pp. 91 - 100
• Main Author: Neri, Filippo
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Agent based modeling; Financial markets; Prediction of the SPDR Gold Trust GLD time series; Simulated annealing
• ISBN: 9783030217327; 3030217329
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-21733-4_7

A computational approach combining machine learning (simulated annealing) and agent based simulation is shown to approximate financial time series. The agent based model allows to simulate the market conditions that produced the financial time series and simulated annealing optimize the parameters for the agent based model. The originality of our approach stays in the combination of financial market simulation with meta-learning of its parameters. The original contribution of the paper stays in discussing how the methodology can be applied under several meta-learning conditions and its experimentation on the real world SPDR Gold Trust (GLD) timeseries.