Non-Linear Interactions and Exchange Rate Prediction: Empirical Evidence Using Support Vector Regression

DOI10.1080/1350486X.2019.1593866zbMath1410.91350OpenAlexW2932407927WikidataQ128098841 ScholiaQ128098841MaRDI QIDQ5378531

Pedro Henrique M. Albuquerque, Peng Yaohao

Publication date: 3 June 2019

Published in: Applied Mathematical Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/1350486x.2019.1593866

zbMATH Keywords

machine learningmacroeconomic fundamentalsforeign exchange marketpredictive abilitykernel functions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Macroeconomic theory (monetary models, models of taxation) (91B64)

Uses Software

• Kernlab
• EasyMKL

Cites Work

• Unnamed Item
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• Support-vector networks
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• A Reality Check for Data Snooping
• Deep learning for finance: deep portfolios
• Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black--Scholes Partial Differential Equations
• Factor Model Forecasts of Exchange Rates

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