FORECASTING STOCK MARKET CRASHES VIA REAL-TIME RECESSION PROBABILITIES: A QUANTUM COMPUTING APPROACH

DOI10.1142/S0218348X22401624OpenAlexW4226466954MaRDI QIDQ5101557

Manuel A. Fernández-Gámez, M. Belén Salas, David Alaminos

Publication date: 30 August 2022

Published in: Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218348x22401624

zbMATH Keywords

forecastingquantum computingsystemic riskquantum neural networksstock market crashesquantum support vector regression

Mathematics Subject Classification ID

Mathematical economics (91Bxx) Applications of statistics (62Pxx) Inference from stochastic processes (62Mxx)

Uses Software

• NumPy
• Sobol

Cites Work

• Global prediction of recessions
• Making best use of model evaluations to compute sensitivity indices
• Model averaging in Markov-switching models: predicting national recessions with regional data
• Crash forecasting in the Korean stock market based on the log-periodic structure and pattern recognition
• A nonstandard finite difference scheme for the modeling and nonidentical synchronization of a novel fractional chaotic system
• A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
• Predicting recessions using trends in the yield spread
• Sobol Sensitivity: A Strategy for Feature Selection

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