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Quantum Neural Networks for Forecasting Inflation Dynamics


Affiliations
1 Department of Mechanical Engineering and Energy Efficiency, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain
2 Department of Economics and Business, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain
3 Department of Finance and Accounting, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain
 

Inflation is a key indicator in the economy that measures the average level of prices of goods and services, being an important ratio in public and private decision-making, so predicting it with precision has always been a concern of economists. This paper makes inflation predictions with different time horizons applying quantum theory through Quantum Neural Networks. The results obtained teach that Quantum Neural Networks overcome the predictive power of the existing models in the previous literature and yields a low-level of errors when predicting any change in the direction of the forecast trend.

Keywords

Inflation Dynamics, Neural Networks, Quantum Computing, Quantum Neural Networks, Macroeconomic Forecasting.
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  • Quantum Neural Networks for Forecasting Inflation Dynamics

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Authors

David Alaminos
Department of Mechanical Engineering and Energy Efficiency, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain
Ignacio Esteban
Department of Economics and Business, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain
M. Belén Salas
Department of Economics and Business, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain
Angela M. Callejón
Department of Finance and Accounting, University of Málaga, Campus El Ejido s/n, 29071 Málaga, Spain

Abstract


Inflation is a key indicator in the economy that measures the average level of prices of goods and services, being an important ratio in public and private decision-making, so predicting it with precision has always been a concern of economists. This paper makes inflation predictions with different time horizons applying quantum theory through Quantum Neural Networks. The results obtained teach that Quantum Neural Networks overcome the predictive power of the existing models in the previous literature and yields a low-level of errors when predicting any change in the direction of the forecast trend.

Keywords


Inflation Dynamics, Neural Networks, Quantum Computing, Quantum Neural Networks, Macroeconomic Forecasting.

References