Quantum Neural Networks for Forecasting Inflation Dynamics
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.
Inflation dynamics, Macroeconomic forecasting, Neural Networks, Quantum Computing, Quantum Neural Networks
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