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Research on exchange rate pass‐through effect based on artificial intelligence approach
Author(s) -
Chen Hong,
Hu WenZhe
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4986
Subject(s) - artificial neural network , exchange rate , computer science , index (typography) , chaotic , artificial intelligence , econometrics , economics , macroeconomics , world wide web
Summary Artificial intelligence is widely believed to reshape many industries in the future. This paper analyzes the chaotic characteristics of Chinese export price index, exchange rate data, and studies the predictive ability of the neural network model in exchange rate passthrough (ERPT) prediction. The Hermite neural network model, one of artificial intelligence models, is selected to forecast the rate of pass‐through effect. Hermite neural network model demonstrates a superior forecasting accuracy, and its forecasting error is less than that of the general neural network model.