Research on exchange rate pass‐through effect based on artificial intelligence approach

Abstract

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.

Testing for Complete Pass-Through of Exchange Rate Without Trade Barriers

“…Indeed, they claimed that misspecification is a curial reason to obtain unreliable exchange rate pass-through estimation. Chen and Hu (2019) showed that neural network model can mitigate the misspecification problem and forecast the exchange rate pass-through effect with higher precision.…”

Special issue on multimodal information learning and analytics on cross‐media big data

“…The hierarchal structure, call routing, and bandwidth usage of the multidomain UC system are studied by Shen et al After describing the architecture of the multidomain UC system, a no‐worse‐than‐two‐hop query algorithm based on P2P is proposed for interdomain call, and it is showed that 80% of users can finish call query in one hop based on the derived performance formulas. Chen and Hu analyzed the chaotic characteristics of Chinese export price index and exchange rate data and studied the predictive ability of the neural network model in exchange rate pass‐through prediction.…”