Explainable artificial intelligence modeling to forecast bitcoin prices

John W. Goodell, Sami Ben Jabeur, Foued Saâdaoui and Muhammad Ali Nasir

International Review of Financial Analysis, 2023, vol. 88, issue C

Abstract: Forecasting cryptocurrency behaviour is an increasingly important issue for investors. However, proposed analytical approaches typically suffer from a lack of explanatory power. In response, we propose for cryptocurrency pricing an explainable artificial intelligence (XAI) framework, including a new feature selection method integrated with a game-theory-based SHapley Additive exPlanations approach and an explainable forecasting framework. This new approach, extendable to other uses, improves both forecasting and model generalizability and interpretability. We demonstrate that XAI modeling is capable of predicting cryptocurrency prices during the recent cryptocurrency downturn identified as associated in part with the Russian-Ukraine war. Modeling reveals the critical inflection points of the daily financial and macroeconomic determinants of the transitions between low and high daily prices. We contribute to financial operating systems research and practice by introducing XAI techniques to enhance the transparency and interpretability of machine learning applications and to support various decision-making processes.

Keywords: Decision support systems; Explainable artificial intelligence; SHAP value; Feature selection; Cryptocurrency prices (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521923002181
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:88:y:2023:i:c:s1057521923002181

DOI: 10.1016/j.irfa.2023.102702

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().