Pages that link to "Item:Q2629659"
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The following pages link to Support vector regression for loss given default modelling (Q2629659):
Displaying 15 items.
- Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research (Q319944) (← links)
- Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms -- support vector regression forecast combinations (Q320100) (← links)
- Sharp asymptotics for large portfolio losses under extreme risks (Q666988) (← links)
- Improving corporate bond recovery rate prediction using multi-factor support vector regressions (Q724157) (← links)
- Systematic effects among loss given defaults and their implications on downturn estimation (Q1653399) (← links)
- Fuzzy decision fusion approach for loss-given-default modeling (Q1683113) (← links)
- European exchange trading funds trading with locally weighted support vector regression (Q1698924) (← links)
- Behaviour-based short-term invoice probability of default evaluation (Q1752908) (← links)
- Loss functions for loss given default model comparison (Q1754331) (← links)
- Using favorite data to analyze asymmetric competition: machine learning models (Q2023935) (← links)
- Intertemporal defaulted bond recoveries prediction via machine learning (Q2060436) (← links)
- Explainable models of credit losses (Q2140185) (← links)
- Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities (Q4554257) (← links)
- (Q5851381) (← links)
- Heterogeneities among credit risk parameter distributions: the modality defines the best estimation method (Q6103193) (← links)
