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Corporate Bankruptcy Prediction : International Trends and Local Experience
| Corporate Bankruptcy Prediction : International Trends and Local Experience |
| Autore | Prusak Błażej |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (202 p.) |
| Soggetto topico | Economics, finance, business & management |
| Soggetto non controllato |
ISA 701
audit expectation gap key audit matters materiality Poland corporate bankruptcy forecasting fuzzy sets artificial neural networks decision trees bankruptcy prediction tax arrears payment defaults financial ratios failure bankruptcy chapter 11 regression count meta-analysis literature review manufacturing insolvency prediction citation mining classification credit risk modelling corporate failure rating systems ensemble classifiers boosting bagging stacking scoring models insolvency financial distress default forecasting methods models predicting financial distress phases of economic cycle Czech Republic European large companies bankruptcy risk company performance Principal Component Analysis neural networks support vector machine bankruptcy model |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Corporate Bankruptcy Prediction |
| Record Nr. | UNINA-9910557527203321 |
Prusak Błażej
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Empirical Finance
| Empirical Finance |
| Autore | Hamori Shigeyuki |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (276 p.) |
| Soggetto non controllato |
short-term forecasting
wavelet transform IPO volatility US dollar institutional investors’ shareholdings neural network financial market stress market microstructure text similarity TVP-VAR model Japanese yen convolutional neural networks global financial crisis deep neural network cross-correlation function boosting causality-in-variance flight to quality bagging earnings quality algorithmic trading stop loss statistical arbitrage ensemble learning liquidity risk premium gold return futures market take profit currency crisis spark spread city banks piecewise regression model financial and non-financial variables exports data mining latency crude oil futures prices forecasting random forests wholesale electricity SVM random forest bank credit deep learning Vietnam inertia MACD initial public offering text mining bankruptcy prediction exchange rate asset pricing model LSTM panel data model structural break credit risk housing and stock markets copula ARDL earnings manipulation machine learning natural gas housing price asymmetric dependence real estate development loans earnings management cointegration predictive accuracy robust regression quantile regression dependence structure housing loans price discovery utility of international currency ATR |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346675203321 |
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Hamori Shigeyuki
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical Methods for the Analysis of Genomic Data
| Statistical Methods for the Analysis of Genomic Data |
| Autore | Jiang Hui |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (136 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
multiple cancer types
integrative analysis omics data prognosis modeling classification gene set enrichment analysis boosting kernel method Bayes factor Bayesian mixed-effect model CpG sites DNA methylation Ordinal responses GEE lipid-environment interaction longitudinal lipidomics study penalized variable selection convolutional neural networks deep learning feed-forward neural networks machine learning gene regulatory network nonparanormal graphical model network substructure false discovery rate control gaussian finite mixture model clustering analysis uncertainty expectation-maximization algorithm classification boundary gene expression RNA-seq |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557545803321 |
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Jiang Hui
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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