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Machine learning risk models
Kakushadze, Zura; Yu, Willie - In: Journal of risk & control 6 (2019) 1, pp. 37-64
Persistent link: https://www.econbiz.de/10012237599
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Predicting daily surgical volumes using probabilistic estimates of providers' future availability
Eun, Joonyup; Tiwari, Vikram; Sandberg, Warren S. - In: Decision sciences 53 (2022) 1, pp. 124-149
Persistent link: https://www.econbiz.de/10013164978
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A probabilistic graphical models approach to model interconnectedness
Denev, Alexander; Papaioannou, Adrien; Angelini, Orazio - In: International journal of risk assessment and management … 23 (2020) 2, pp. 119-133
Persistent link: https://www.econbiz.de/10012256731
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Dynamic Factor Trees and Forests : a theory-led machine learning framework for non-linear and state-dependent short-term U.S. GDP growth predictions
Wochner, Daniel - 2020 - This version: January 31, 2020
theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic … reduce to the standard Dynamic Factor Model (DFM) as a special case and allow us to embed theory-led factor models in …
Persistent link: https://www.econbiz.de/10012172506
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Probabilistic recalibration of forecasts
Graziani, Carlo; Rosner, Robert; Adams, Jennifer M.; … - In: International journal of forecasting 37 (2021) 1, pp. 1-27
Persistent link: https://www.econbiz.de/10012692513
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Profit-based churn prediction based on Minimax Probability Machines
Maldonado, Sebastián; López, Julio; Vairetti, Carla - In: European journal of operational research : EJOR 284 (2020) 1, pp. 273-284
Persistent link: https://www.econbiz.de/10012238668
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Machine-learning classifiers for imbalanced tornado data
Trafalis, Theodore B.; Adrianto, Indra; Richman, Michael B. - In: Computational Management Science : CMS 11 (2014) 4, pp. 403-418
Persistent link: https://www.econbiz.de/10010437151
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Correlation analysis of forecasting methods : the case of the M4 competition
Agathangelou, Pantelis; Trihinas, Demetris; Katakis, Ioannis - In: International journal of forecasting 36 (2020) 1, pp. 212-216
Persistent link: https://www.econbiz.de/10012414644
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Can machine learning-based portfolios outperform traditional risk-based portfolios? : the need to account for covariance misspecification
Jain, Prayut; Jain, Shashi - In: Risks : open access journal 7 (2019) 3/74, pp. 1-27
theory and machine learning to build a diversified portfolio. Like the traditional risk-based allocation methods, HRP is also …
Persistent link: https://www.econbiz.de/10012127594
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Machine Learning for Corporate Default Risk : Multi-Period Prediction, Frailty Correlation, Loan Portfolios, and Tail Probabilities
Sigrist, Fabio; Leuenberger, Nicola - 2021
tails of portfolio losses compared to both a linear frailty model and machine learning methods ignoring frailty correlation …
Persistent link: https://www.econbiz.de/10013324358