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Incorporating financial development indicators into early warning systems

Author

Listed:
  • Alexey Ponomarenko

    (Bank of Russia, Russian Federation)

  • Stas Tatarintsev

    (Bank of Russia, Russian Federation)

Abstract
We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators (e.g. levels of credit to GDP ratio) in addition to conventional imbalances measures (e.g. credit gaps). The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that combining financial imbalances and financial development indicators helps to improve the out-of-sample accuracy of the early warning system

Suggested Citation

  • Alexey Ponomarenko & Stas Tatarintsev, 2020. "Incorporating financial development indicators into early warning systems," Bank of Russia Working Paper Series wps58, Bank of Russia.
    • Handle: RePEc:bkr:wpaper:wps58
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    2. Nguyen, Hoai Thi Thanh & Tram, Huong Thi Xuan & Nguyen, Linh Thi Thuy, 2023. "Interest rates and systemic risk:Evidence from the Vietnamese economy," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    3. Andrzej Cichoń & Michał Włodarz, 2023. "OLTC Fault detection Based on Acoustic Emission and Supported by Machine Learning," Energies, MDPI, vol. 17(1), pages 1-14, December.

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    More about this item

    Keywords

    Early warning indicators; financial crisis; financial development; credit gap; random forest;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G01 - Financial Economics - - General - - - Financial Crises
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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