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Evaluating the resilience of clean funds amidst COVID-19 and the Russia-Ukraine war: a consensus between time varying models and machine learning techniques

Sudhi Sharma et al.

Environmental Economics and Policy Studies2026https://doi.org/10.1007/s10018-026-00465-8article
AJG 1ABDC B
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https://doi.org/https://doi.org/10.1007/s10018-026-00465-8

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@article{sudhi2026,
  title        = {{Evaluating the resilience of clean funds amidst COVID-19 and the Russia-Ukraine war: a consensus between time varying models and machine learning techniques}},
  author       = {Sudhi Sharma et al.},
  journal      = {Environmental Economics and Policy Studies},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10018-026-00465-8},
}

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Evaluating the resilience of clean funds amidst COVID-19 and the Russia-Ukraine war: a consensus between time varying models and machine learning techniques

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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

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