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Time-varying autoregressive distributed lag model with changing volatility for stress test

Author

Listed:
  • Zhou, Leilei

    (Quantitative Researcher, Department of Applied Mathematics and Statistics at State University of New York at Stony Brook, USA)

  • Zhu, Wei

    (Professor and Graduate Programme Director in the Department of Applied Mathematics and Statistics at the Center for Finance, State University of New York at Stony Brook, USA)

Abstract

We present a novel time-varying autoregressive distributed lag (TV-ADL) model that allows for changes in both transmission mechanisms and innovation volatilities. The forecasting performance of the TV-ADL model has been substantially improved by removing the unrealistic traditional assumptions of constant volatility and constant inter-variable relationship. Our model is further adapted to stress tests mandated by the US Federal Reserve to generate conditional forecasts of the pre-provision net revenue of financial holding companies with large assets. The improvement of forecasting performance is demonstrated by the significant reduction of out-of-sample forecast errors at different horizons.

Suggested Citation

  • Zhou, Leilei & Zhu, Wei, 2021. "Time-varying autoregressive distributed lag model with changing volatility for stress test," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 14(2), pages 195-208, March.
    • Handle: RePEc:aza:rmfi00:y:2021:v:14:i:2:p:195-208
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    More about this item

    Keywords

    financial supervision; stress tests; time-varying parameter; forecast; volatilities;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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