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Credit spreads and systematic risk in the U.S. banking industry : a neural network model approach
Anderson, Mark A.; Maurer, Frantz - In: The journal of applied business research 31 (2015) 5, pp. 1799-1806
Persistent link: https://www.econbiz.de/10011412447
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Marktorientierte Kreditrisikobewertung : eine empirische Untersuchung mittels künstlicher neuronaler Netze
Siemes, Andreas - 2002
Persistent link: https://www.econbiz.de/10001637523
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Marktorientierte Kreditrisikobewertung : eine empirische Untersuchung mittels künstlicher neuronaler Netze
Siemes, Andreas - 2002
Kreditinstitute werden heute vor die Herausforderung gestellt, einen effektiven und effizienten Risikomanagementprozess zu etablieren. Insbesondere bei der Bewertung von Unternehmensanleihen und Krediten wird diese Notwendigkeit deutlich. Die Arbeit greift diese Problemstellung auf, indem ein...
Persistent link: https://www.econbiz.de/10011920898
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Regularizing Bayesian predictive regressions
Feng, Guanhao; Polson, Nicholas G. - In: The journal of asset management 21 (2020) 7, pp. 591-608
Persistent link: https://www.econbiz.de/10012421072
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The equity premium puzzle: an artificial neural network approach
Wong, Shee Q.; Hassan, Nik R.; Feroz, Ehsan H. - In: Review of accounting & finance 6 (2007) 2, pp. 150-161
Persistent link: https://www.econbiz.de/10003490027
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The relationship between market sentiment and equity premium : an artificial neural network analysis
Hassan, Nik R.; Wong, Shee Q. - In: International journal of electronic finance : IJEF 2 (2008) 2, pp. 227-240
Persistent link: https://www.econbiz.de/10003703766
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Forecasting the market risk premium with artificial neural networks
Oikonomikou, Leoni Eleni - 2016 - Revised version: November 2015
This paper aims to forecast the Market Risk premium (MRP) in the US stock market by applying machine learning …). Furthermore, Univariate ARMA and Exponential Smoothing models are also tested. The Market Risk Premium is defined as the … forecast the Market Risk Premium in a daily basis using Artificial Neural Networks (ANNs). Second, it is not based on a …
Persistent link: https://www.econbiz.de/10011454074
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Neural model identification, variable selection and model adequacy
Refenes, Apostolos-Paul; Zapranis, Achilleas - In: Journal of forecasting 18 (1999) 5, pp. 299-332
Persistent link: https://www.econbiz.de/10001433936
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The Equity Premium Puzzle : An Artificial Neural Network Approach
Wong, Shee Q. - 2019
This paper presents evidence suggesting that artificial neural networks approach (ANNs) outperform traditional statistical methods and can forecast equity premiums reasonably well. The study replicates out-of-sample estimates of regression using ANN with economic fundamentals as inputs. The...
Persistent link: https://www.econbiz.de/10012895878
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Empirical asset pricing via machine learning
Gu, Shihao; Kelly, Bryan T.; Xiu, Dacheng - In: The review of financial studies 33 (2020) 5, pp. 2223-2273
Persistent link: https://www.econbiz.de/10012244733