arbiter
JournalsAccount

Decoding Market Prices of Sustainable Cryptocurrencies: Fresh Insights from Ensemble Machine Learning and Explainable AI

Indranil Ghosh et al.

Global Business Review2026https://doi.org/10.1177/09721509261427956article
AJG 1ABDC B
Weight
0.50

Abstract

This research develops an integrated framework that combines ensemble machine learning and explainable artificial intelligence to predict the performance of sustainable cryptocurrencies, including Avalanche, Build and Build (BNB) Chain, Polkadot and Solana, and to reveal the dependencies between these assets and key explanatory features. The framework employs a comprehensive predictive structure that integrates supervised and unsupervised feature processing with a metaheuristic-tuned ensemble learning model. BorutaShap identifies significant explanatory variables, while isometric mapping obtains an optimized feature representation. Predictions are generated using the Extreme Gradient Boosting algorithm, with hyperparameters optimized through particle swarm optimization. To ensure interpretability, the predictive methodology undergoes rigorous analysis using multiple explainable artificial intelligence techniques that decode dependency patterns at both global and local levels, facilitating a comprehensive understanding of market dynamics for the selected assets. Results reveal that market sentiment, technological outlook and US options market fear are the primary determinants of sustainable crypto asset performance.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1177/09721509261427956

Or copy a formatted citation

@article{indranil2026,
  title        = {{Decoding Market Prices of Sustainable Cryptocurrencies: Fresh Insights from Ensemble Machine Learning and Explainable AI}},
  author       = {Indranil Ghosh et al.},
  journal      = {Global Business Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/09721509261427956},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Decoding Market Prices of Sustainable Cryptocurrencies: Fresh Insights from Ensemble Machine Learning and Explainable AI

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.