SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Financial distress prediction using support vector machines: Ensemble vs. individual
16 references·16 citing·23 second hopsampled
Financial distress prediction using support vector machines: Ensemble vs. individual (2012)Financial distress prediction using suppo…Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Using neural network ensemble…A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy (2006)A real-valued genetic algorit…Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Bankruptcy prediction using s…An application of support vector machines in bankruptcy prediction model (2004)An application of support vec…A genetic algorithm application in bankruptcy prediction modeling (2002)A genetic algorithm applicati…Bankruptcy prediction for credit risk using neural networks: A survey and new results (2001)Bankruptcy prediction for cre…Business failure prediction using rough sets (1999)Business failure prediction u…Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis (1999)Artificial neural networks in…Forecasting with neural networks (1993)Forecasting with neural netwo…Chaos and Nonlinear Dynamics: Application to Financial Markets (1991)Chaos and Nonlinear Dynamics:…A neural network model for bankruptcy prediction (1990)A neural network model for ba…ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS (1985)ASSESSING THE VULNERABILITY T…Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Financial Ratios and the Prob…ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)ZETATM analysis A new model t…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Financial Ratios As Predictors of Failure (1966)Financial Ratios As Predictor…Interpreting the prediction results of the tree‐based gradient boosting models for financial distress prediction with an explainable machine learning approach (2022)Interpreting the prediction r…The application of PROMETHEE multi-criteria decision aid in financial decision making: Case of distress prediction models evaluation (2020)The application of PROMETHEE …Financial distress prediction: Regularized sparse-based Random Subspace with ER aggregation rule incorporating textual disclosures (2020)Financial distress prediction…Corporate failure prediction models in the twenty-first century: a review (2020)Corporate failure prediction …A novel hybrid credit scoring model based on ensemble feature selection and multilayer ensemble classification (2019)A novel hybrid credit scoring…The effects of handling outliers on the performance of bankruptcy prediction models (2018)The effects of handling outli…Predicting financial distress of contractors in the construction industry using ensemble learning (2018)Predicting financial distress…Financial crisis prediction model using ant colony optimization (2018)Financial crisis prediction m…Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction (2018)Exploring the synergetic effe…Probabilistic modeling and visualization for bankruptcy prediction (2017)Probabilistic modeling and vi…Credit default prediction modeling: an application of support vector machine (2017)Credit default prediction mod…Using an ensemble classifier based on sequential floating forward selection for financial distress prediction problem (2016)Using an ensemble classifier …Financial distress prediction using the hybrid associative memory with translation (2016)Financial distress prediction…An Effective Computational Model for Bankruptcy Prediction Using Kernel Extreme Learning Machine Approach (2016)An Effective Computational Mo…A two-stage classification technique for bankruptcy prediction (2016)A two-stage classification te…Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal (2015)Enhancing accuracy and interp…Conditional logit analysis of qualitative choice behavior (1972)The Effect of Audit Quality on Earnings Management* (1998)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Bayesian Analysis of Stochastic Volatility Models (1994)Parametric and Nonparametric Volatility Measurement (2010)Does realized skewness predict the cross-section of equity returns? (2015)Positive Accounting Theory (1985)Designing a neural network for forecasting financial and economic time series (1996)Forecasting with artificial neural networks: (1998)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review (2020)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Forecasting Bankruptcy More Accurately: A Simple Hazard Model (2001)In Search of Distress Risk (2008)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)Consumer credit-risk models via machine-learning algorithms (2010)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Managerial incentives and risk-taking☆ (2005)How does financial reporting quality relate to investment efficiency? (2009)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy6,005 cited
  • 1966Financial Ratios As Predictors of Failure4,753 cited
  • 1977ZETATM analysis A new model to identify bankruptcy risk of corporations1,812 cited
  • 1991Chaos and Nonlinear Dynamics: Application to Financial Markets1,046 cited
  • 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters872 cited
  • 1990A neural network model for bankruptcy prediction853 cited
  • 2004An application of support vector machines in bankruptcy prediction model809 cited
  • 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results696 cited
  • 1999Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis677 cited
  • 1985ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS559 cited
  • 2007Using neural network ensembles for bankruptcy prediction and credit scoring514 cited
  • 1999Business failure prediction using rough sets493 cited
  • 1993Forecasting with neural networks432 cited
  • 2002

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

A genetic algorithm application in bankruptcy prediction modeling
386 cited
  • 2006A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy381 cited
  • Cited by

    • 2016A two-stage classification technique for bankruptcy prediction142 cited
    • 2018Financial crisis prediction model using ant colony optimization139 cited
    • 2018Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction138 cited
    • 2015Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal109 cited
    • 2018The effects of handling outliers on the performance of bankruptcy prediction models98 cited
    • 2018Predicting financial distress of contractors in the construction industry using ensemble learning91 cited
    • 2017Probabilistic modeling and visualization for bankruptcy prediction90 cited
    • 2016Financial distress prediction using the hybrid associative memory with translation83 cited
    • 2016An Effective Computational Model for Bankruptcy Prediction Using Kernel Extreme Learning Machine Approach82 cited
    • 2020The application of PROMETHEE multi-criteria decision aid in financial decision making: Case of distress prediction models evaluation82 cited
    • 2016Using an ensemble classifier based on sequential floating forward selection for financial distress prediction problem77 cited
    • 2019A novel hybrid credit scoring model based on ensemble feature selection and multilayer ensemble classification73 cited
    • 2020Corporate failure prediction models in the twenty-first century: a review68 cited
    • 2017Credit default prediction modeling: an application of support vector machine65 cited
    • 2022Interpreting the prediction results of the tree‐based gradient boosting models for financial distress prediction with an explainable machine learning approach62 cited
    • 2020Financial distress prediction: Regularized sparse-based Random Subspace with ER aggregation rule incorporating textual disclosures57 cited