Pages that link to "Item:Q869139"
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The following pages link to Bankruptcy prediction in banks and firms via statistical and intelligent techniques -- a review (Q869139):
Displaying 50 items.
- The financing of innovative SMEs: a multicriteria credit rating model (Q319403) (← links)
- Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research (Q319944) (← links)
- A data analytic approach to forecasting daily stock returns in an emerging market (Q323244) (← links)
- Empirical models based on features ranking techniques for corporate financial distress prediction (Q356191) (← links)
- Real-time fuzzy regression analysis: a convex hull approach (Q541718) (← links)
- Bankruptcy prediction using terminal failure processes (Q726265) (← links)
- Business failure prediction using hybrid\(^2\) case-based reasoning (H\(^2\)CBR) (Q733532) (← links)
- Firm credit risk evaluation: a series two-stage DEA modeling framework (Q889566) (← links)
- A hybrid approach using two-level DEA for financial failure prediction and integrated SE-DEA and GCA for indicators selection (Q903023) (← links)
- Financial distress early warning based on group decision making (Q955623) (← links)
- DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique (Q958086) (← links)
- Hybridizing principles of the Electre method with case-based reasoning for data mining: Electre-CBR-I and Electre-CBR-II (Q1011284) (← links)
- Evaluation of credit risk based on firm performance (Q1038348) (← links)
- Methodological comparison between DEA (data envelopment analysis) and DEA-DA (discriminant analysis) from the perspective of bankruptcy assessment (Q1042177) (← links)
- DEA-DA for bankruptcy-based performance assessment: misclassification analysis of Japanese construction industry (Q1042178) (← links)
- Soft computing hybrids for FOREX rate prediction: a comprehensive review (Q1654378) (← links)
- Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions (Q1730582) (← links)
- A nearest neighbour extension to project duration forecasting with artificial intelligence (Q1751933) (← links)
- The effectiveness of TARP-CPP on the US banking industry: a new copula-based approach (Q1752290) (← links)
- Nonstationary Z-score measures (Q1753443) (← links)
- A corporate credit rating model using multi-class support vector machines with an ordinal pairwise partitioning approach (Q1761095) (← links)
- A corporate credit rating model using support vector domain combined with fuzzy clustering algorithm (Q1954637) (← links)
- Forecasting corporate failure using ensemble of self-organizing neural networks (Q2028771) (← links)
- Exchange rate forecasting using ensemble modeling for better policy implications (Q2046053) (← links)
- Bankruptcy prediction: evidence from Vietnam (Q2086202) (← links)
- Extending business failure prediction models with textual website content using deep learning (Q2106750) (← links)
- Banks to basics! Why banking regulation should focus on equity (Q2140179) (← links)
- Credit default prediction from user-generated text in peer-to-peer lending using deep learning (Q2140350) (← links)
- Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis (Q2159559) (← links)
- Cost-sensitive business failure prediction when misclassification costs are uncertain: a heterogeneous ensemble selection approach (Q2183867) (← links)
- Suppliers' trade credit strategies with transparent credit ratings: null, exclusive, and nonchalant provision (Q2242201) (← links)
- Forecast bankruptcy using a blend of clustering and MARS model: case of US banks (Q2288890) (← links)
- An improved grasshopper optimization algorithm with application to financial stress prediction (Q2307043) (← links)
- Bankruptcy prediction in firms with statistical and intelligent techniques and a comparison of evolutionary computation approaches (Q2429099) (← links)
- Assessing bank efficiency and performance with operational research and artificial intelligence techniques: a survey (Q2655605) (← links)
- FUZZY, DISTRIBUTED, INSTANCE COUNTING, AND DEFAULT ARTMAP NEURAL NETWORKS FOR FINANCIAL DIAGNOSIS (Q3063637) (← links)
- Short term prediction of extreme returns based on the recurrence interval analysis (Q4554428) (← links)
- Design of adaptive Elman networks for credit risk assessment (Q4991078) (← links)
- Modelling the Cognitive Financial Group Interconnected Risk Network (Q5095373) (← links)
- The comparison of enterprise bankruptcy forecasting method (Q5124760) (← links)
- A new financial stress index model based on support vector regression and control chart (Q5130192) (← links)
- Sector categorization using gradient boosted trees trained on fundamental firm data (Q5156839) (← links)
- Bankruptcy prediction using SVM models with a new approach to combine features selection and parameter optimisation (Q5172554) (← links)
- Prediction of bankruptcy using support vector machines: an application to bank bankruptcy (Q5218886) (← links)
- EMPIRICAL STUDIES OF STRUCTURAL CREDIT RISK MODELS AND THE APPLICATION IN DEFAULT PREDICTION: REVIEW AND NEW EVIDENCE (Q5305098) (← links)
- Cutoff Threshold Decisions for Classification Algorithms with Risk Aversion (Q5868894) (← links)
- Machine learning in corporate credit rating assessment using the expanded audit report (Q6097105) (← links)
- The data sampling effect on financial distress prediction by single and ensemble learning techniques (Q6107618) (← links)
- Designing topological data to forecast bankruptcy using convolutional neural networks (Q6115949) (← links)
- New metrics and approaches for predicting bankruptcy (Q6172619) (← links)
