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2022-06-27

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(c) World Scientific Publishing, 2022
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/198402

Forecasting Stock Market Crashes via Real-Time Recession Probabilities: A Quantum Computing Approach

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https://doi.org/10.1142/S0218348X22401624

Abstract

A fast and precise prediction of stock market crashes is an important aspect of economic growth, fiscal and monetary system because it facilitates the government the application of suitable policies. Many works have examined the behaviour of the fall of stock markets and have built models to predict them. Nevertheless, there are limitations to the available research, and the literature calls for more investigation on the topic, as currently the accuracy of the models remains low and they have only been extended for the largest economies. This study provides a comparison of Quantum forecast methods stock market declines and, therefore, a new prediction model of stock market crashes via real-time recession probabilities with the power to accurately estimate future global stock market downturn scenarios. A 104-country sample has been used, allowing the sample compositions to take into account the regional diversity of the alert warning indicators. To obtain a robust model, several alternative techniques have been employed on the sample under study, being Quantum Boltzmann Machines, which have obtained very good prediction results due to their ability to remember features and develop long-term dependencies from time series and sequential data. Our model has large policy implications for the appropriate macroeconomic policy response to downside risks, offering tools to help achieve financial stability at the international level.

Subject

Previsió econòmica, Anàlisi de regressió, Anàlisi vectorial

Subject (English)

Economic forecasting, Regression analysis, Vector analysis

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Articles publicats en revistes (Empresa)

Citation

ALAMINOS AGUILERA, David, SALAS COMPAS, M. Belén and FERNÁNDEZ-GÁMEZ, Manuel A. Forecasting Stock Market Crashes via Real-Time Recession Probabilities: A Quantum Computing Approach. Fractals-Complex Geometry Patterns and Scaling in Nature and Society. 2022. Vol. 30, num. 05, pags. 2240162. ISSN 0218-348X. [consulted: 14 of August of 2026]. Available at: https://hdl.handle.net/2445/198402

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