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Fan charts in era of big data and learning

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    0581659 - ÚTIA 2025 RIV NL eng J - Journal Article
    Baruník, Jozef - Hanus, Luboš
    Fan charts in era of big data and learning.
    Finance Research Letters. Roč. 61, č. 1 (2024), č. článku 105003. ISSN 1544-6123. E-ISSN 1544-6131
    R&D Projects: GA ČR(CZ) GX19-28231X
    Institutional support: RVO:67985556
    Keywords : Fan charts * Probabilistic forecasting * Machine learning
    OECD category: Applied Economics, Econometrics
    Impact factor: 10.4, year: 2022
    Method of publishing: Limited access
    https://www.sciencedirect.com/science/article/pii/S1544612324000333?dgcid=author http://library.utia.cas.cz/separaty/2023/E/barunik-0581659.pdf

    We propose how to construct big data-driven macroeconomic fan charts, using machine learning methods to reflect the information in 216 relevant economic variables. Such data-rich fan charts do not rely on restrictive model assumptions and allow the exploration of non-Gaussian, asymmetric, heavy-tailed data and their non-linear interactions. By allowing complex patterns to be learned from a data-rich environment, our fan charts are useful for decision making that depends on the uncertainty of a potentially large number of economic variables — most public policy issues.
    Permanent Link: https://hdl.handle.net/11104/0349774

     
     
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