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Forecasting value-at-risk under temporal and portfolio aggregation
Kole, Erik; Markwat, Thijs; Opschoor, Anne; Dijk, Dick van - 2015
We examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a … based on asset class, or into a single portfolio. We compare the impact of aggregation to that of choosing a model for the … that the degree of temporal aggregation is most important. Daily returns form the best basis for VaR forecasts. Modelling …
Persistent link: https://www.econbiz.de/10011431503
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A new feature selection technique applied to credit scoring data using a rank aggregation approach based on optimization, genetic algorithm, and similarity
Bouaguel, Waad; Mufti, Ghazi Bel; Limam, Mohamed - In: Knowledge discovery process and methods to enhance …, (pp. 347-375). 2015
Persistent link: https://www.econbiz.de/10012123362
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Forecasting value-at-risk under temporal and portfolio aggregation
Kole, Erik; Markwat, Thijs; Opschoor, Anne; Dijk, Dick van - In: Journal of financial econometrics : official journal of … 15 (2017) 4, pp. 649-677
Persistent link: https://www.econbiz.de/10011987663
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Forecasting aggregates with disaggregate variables : does boosting help to select the most relevant predictors?
Zeng, Jing - In: Journal of forecasting 36 (2017) 1, pp. 74-90
Persistent link: https://www.econbiz.de/10011729069
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The scale of predictability
Bandi, Federico M.; Perron, Bernard; Tamoni, Andrea; … - 2013 - This version: December 19, 2013
Persistent link: https://www.econbiz.de/10011813907
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Forecasting aggregates with disaggregate variables : does boosting help to select the most informative predictors? ; conference paper
Zeng, Jing - 2014
Including disaggregate variables or using information extracted from the disaggregate variables into a forecasting model for an eco- nomic aggregate may improve the forecasting accuracy. In this paper we suggest to use boosting as a method to select the disaggregate variables which are most...
Persistent link: https://www.econbiz.de/10010482520
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Two reasons to make aggregated probability forecasts more extreme
Baron, Jonathan; Mellers, Barbara A.; Tetlock, Philip E.; … - In: Decision analysis : a journal of the Institute for … 11 (2014) 2, pp. 133-145
Persistent link: https://www.econbiz.de/10010382759
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Hidden experts in the crowd : using meta-predictions to leverage expertise in single-question prediction problems
Wilkening, Tom; Martinie, Marcellin; Howe, Piers D. L. - In: Management science : journal of the Institute for … 68 (2022) 1, pp. 487-508
Persistent link: https://www.econbiz.de/10012821209
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Demand forecasting in supply chains : a review of aggregation and hierarchical approaches
Babai, M. Zied; Boylan, John E.; Rostami-Tabar, Bahman - In: International journal of production research 60 (2022) 1, pp. 324-348
Persistent link: https://www.econbiz.de/10012873142
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Weigh(t)ing the basket : aggregate and component-based inflation forecasts for the euro area
Chalmovianský, Jakub; Porqueddu, Mario; Sokol, Andrej - 2020
We compare direct forecasts of HICP and HICP excluding energy and food in the euro area and five member countries to aggregated forecasts of their main components from large Bayesian VARs with a shared set of predictors. We focus on conditional point and density forecasts, in line with...
Persistent link: https://www.econbiz.de/10012384462