ArticleFrontiers in artificial intelligence2025
Explainable machine learning to predict the cost of capital.
Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Nature-inspired multi-objective artificial intelligence for short-horizon volatility-regime early warning and defensive asset allocation.Frontiers in artificial intelligence · 2026Article
- Non-linear impacts of local fiscal expenditure on farmers' income: A SHAP-informed machine-learning analysis.PloS one · 2026Article
- Frequency of diseases and use of medicinal plants in adults in a rural Peruvian community.Frontiers in public health · 2026Article
- Development of a machine learning-based classification model for diabetic foot in patients with type 2 diabetes: an exploratory analysis with SHAP interpretation.Frontiers in medicine · 2026Article
- Predicting BRICS NIFTY50 returns using XAI and S.A.F.E AI lens.Frontiers in artificial intelligence · 2025Article
- Artificial intelligence adoption and corporate ESG performance: evidence from a refined large language model.Frontiers in artificial intelligence · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigates the impact of financial and non-financial factors on a firm's ex-ante cost of capital, which is the reflection of investors' perception on a firm's riskiness. Departing from previous literature, we apply the XGBoost algorithm and two explainable Artificial Intelligence methods, namely the Shapley value approach and Lorenz Model Selection to a sample of more than 1,400 listed companies worldwide. Results confirm the relevance of key financial indicators such as firm size, ROE, firm portfolio risk, but also individuate firm's non-financial features and country's institutional quality as relevant predictors for the cost of capital. These results suggest the importance of non-financial indicators and country institutional quality on the firm's ex-ante cost of equity that expresses investors' risk perception. Our findings pave the way for future investigations on the impact of ESG and country factors in predicting the cost of capital.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.