Author
Listed:
- DAVID ALAMINOS
(Departament d’Empresa, Universitat de Barcelona, Barcelona, Spain†Cátedra de EconomÃa y Finanzas Sostenibles, Universidad de Málaga, Málaga, Spain)
- M. BELÉN SALAS
(��Cátedra de EconomÃa y Finanzas Sostenibles, Universidad de Málaga, Málaga, Spain‡Departamento de Finanzas y Contabilidad, Universidad de Málaga, Málaga, Spain)
- MANUEL A. FERNÃ NDEZ-GÃ MEZ
(��Cátedra de EconomÃa y Finanzas Sostenibles, Universidad de Málaga, Málaga, Spain‡Departamento de Finanzas y Contabilidad, Universidad de Málaga, Málaga, Spain)
Abstract
A fast and precise prediction of stock market crashes is an important aspect of economic growth, fiscal and monetary systems because it facilitates the government in the application of suitable policies. Many works have examined the behavior 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 and 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 is achieved. 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.
Suggested Citation
David Alaminos & M. Belã‰N Salas & Manuel A. Fernã Ndez-Gã Mez, 2022.
"Forecasting Stock Market Crashes Via Real-Time Recession Probabilities: A Quantum Computing Approach,"
FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(05), pages 1-16, August.
Handle:
RePEc:wsi:fracta:v:30:y:2022:i:05:n:s0218348x22401624
DOI: 10.1142/S0218348X22401624
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