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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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Quantitative Methods for Economics and Finance
| Quantitative Methods for Economics and Finance |
| Autore | Trinidad-Segovia J.E |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (418 p.) |
| Soggetto topico | Coins, banknotes, medals, seals (numismatics) |
| Soggetto non controllato |
academic cheating
tax evasion informality pairs trading hurst exponent financial markets long memory co-movement cointegration risk delay decision-making process probability discount detection mean square error multicollinearity raise regression variance inflation factor derivation intertemporal choice decreasing impatience elasticity GARCH EGARCH VaR historical simulation approach peaks-over-threshold EVT student t-copula generalized Pareto distribution centered model noncentered model intercept essential multicollinearity nonessential multicollinearity commodity prices futures prices number of factors eigenvalues volatility cluster Hurst exponent FD4 approach volatility series probability of volatility cluster S& P500 Bitcoin Ethereum Ripple bitcoin deep learning deep recurrent convolutional neural networks forecasting asset pricing financial distress prediction unconstrained distributed lag model multiple periods Chinese listed companies cash flow management corporate prudential risk the financial accelerator financial distress induced risk aversion liquidity constraints liquidity risk macroeconomic propagation multiperiod financial management non-linear macroeconomic modelling Tobin’s q precautionary savings pharmaceutical industry scale economies profitability biotechnological firms non-parametric efficiency productivity DEA dispersion trading option arbitrage volatility trading correlation risk premium econometrics computational finance ensemble empirical mode decomposition (EEMD) autoregressive integrated moving average (ARIMA) support vector regression (SVR) genetic algorithm (GA) energy consumption cryptocurrency gold P 500 DCC copula copulas Markov Chain Monte Carlo simulation local optima vs. local minima SRA approach foreign direct investment bilateral investment treaties regional trade agreements structural gravity model policy uncertainty stock prices dynamically simulated autoregressive distributed lag (DYS-ARDL) threshold regression United States |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557564003321 |
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Trinidad-Segovia J.E
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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