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Editorial for Special Issue “New Frontiers in Forecasting the Business Cycle and Financial Markets”

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  • Alessia Paccagnini

    (Michael Smurfit Graduate Business School, University College Dublin, 94568 Dublin, Ireland
    Centre for Applied Macroeconomic Analysis, Australian National University, Canberra, ACT 0200, Australia)

Abstract

The global financial crisis of 2007–2009 and the COVID-19 pandemic have heightened uncertainty in financial markets and the business cycle [...]

Suggested Citation

  • Alessia Paccagnini, 2021. "Editorial for Special Issue “New Frontiers in Forecasting the Business Cycle and Financial Markets”," Forecasting, MDPI, vol. 3(3), pages 1-3, July.
    • Handle: RePEc:gam:jforec:v:3:y:2021:i:3:p:30-500:d:588484
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    References listed on IDEAS

    as
    1. Janis Bauer & Holger Fink & Eva Stoller, 2020. "Are Issuer Margins Fairly Stated? Evidence from the Issuer Estimated Value for Retail Structured Products," Forecasting, MDPI, vol. 2(4), pages 1-23, September.
    2. Stelios Bekiros & Christos Avdoulas, 2020. "Revisiting the Dynamic Linkages of Treasury Bond Yields for the BRICS: A Forecasting Analysis," Forecasting, MDPI, vol. 2(2), pages 1-28, May.
    3. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    4. Marcel Ausloos, 2020. "Valuation Models Applied to Value-Based Management—Application to the Case of UK Companies with Problems," Forecasting, MDPI, vol. 2(4), pages 1-17, December.
    5. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    6. Angeliki Papana & Anastasia Spyridou, 2020. "Bankruptcy Prediction: The Case of the Greek Market," Forecasting, MDPI, vol. 2(4), pages 1-21, December.
    7. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
    8. Alexander Faehnle & Mariangela Guidolin, 2021. "Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes," Forecasting, MDPI, vol. 3(1), pages 1-15, March.
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