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Tales from tails : on the empirical distributions of forecasting errors and their implication to risk

Spiliotis, Evangelos; Nikolopoulos, Konstantinos; … - In: International journal of forecasting 35 (2019) 2, pp. 687-698

Persistent link: https://www.econbiz.de/10012300716

Leading indicators and maritime safety: predicting future risk with a machine learning approach

Kretschmann, Lutz - In: Journal of shipping and trade 5 (2020) 19, pp. 1-22

continue this development in the future, innovative leading risk indicators can make a significant contribution. If designed … leading risk indicators is positively influenced by the ongoing digital transformation in the maritime industry. With an … increasing amount of data from ship operation becoming available, these can be exploited in innovative risk management solutions …

Persistent link: https://www.econbiz.de/10012301416

Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions

Szubzda, Filip; Chlebus, Marcin - In: Central European economic journal 6 (2019) 53, pp. 70-85

The aim of the presented study was to assess the quality of VaR forecasts in various states of the economic situation. Two approaches based on the extreme value theory were compared: Block Maxima and the Peaks Over Threshold. Forecasts were made on the daily closing prices of 10 major indices in...

Persistent link: https://www.econbiz.de/10012302139

Forecasting high-frequency risk measures

Banulescu, Denisa; Colletaz, Gilbert; Hurlin, Christophe; … - In: Journal of forecasting 35 (2016) 3, pp. 224-249

Persistent link: https://www.econbiz.de/10011580273

Expert judgement for dependence in probabilistic modelling : a systematic literature review and future research directions

Werner, Christoph; Bedford, Tim; Cooke, Roger M.; … - In: European journal of operational research : EJOR 258 (2017) 3, pp. 801-819

Persistent link: https://www.econbiz.de/10011644481

A longevity basis risk analysis in a joint FDM framework

D'Amato, Valeria; Coppola, Mariarosaria; Levantesi, Susanna - In: Journal of risk finance : the convergence of financial … 18 (2017) 1, pp. 55-75

Persistent link: https://www.econbiz.de/10011653711

Forecasting compositional risk allocations

Boonen, Tim J.; Guillén, Montserrat; Santolino, Miguel - In: Insurance / Mathematics & economics 84 (2019), pp. 79-86

Persistent link: https://www.econbiz.de/10011990442

Developing a Bayesian belief network model for prediction of R&D project success

Sharma, Satyendra Kumar; Chanda, Udayan - In: Journal of management analytics 4 (2017) 3, pp. 321-344

Persistent link: https://www.econbiz.de/10011844347

Predicting the impact of multiple risks on project performance : a scenario-based approach

Bañuls, Victor A.; López, Cristina; Turoff, Murray; … - In: Project management journal : PMJ 48 (2017) 5, pp. 95-114

Persistent link: https://www.econbiz.de/10011756024

Real-time assessment and prediction on maritime risk state on the Arctic Route

Zhang, Ye; Hu, Hao; Dai, Lei - In: Maritime policy & management 47 (2020) 3, pp. 352-370

Persistent link: https://www.econbiz.de/10012210405