AI RESEARCH
Neural ARFIMA model for forecasting BRIC exchange rates with long memory
arXiv CS.LG
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ArXi:2509.06697v2 Announce Type: replace-cross Accurate forecasting of exchange rates remains a persistent challenge, particularly for emerging economies such as Brazil, Russia, India, and China (BRIC). These series exhibit long memory and nonlinearity that conventional time series models struggle to capture. Exchange rate dynamics are further influenced by several key drivers, including global economic policy uncertainty, US equity market volatility, US monetary policy uncertainty, oil price growth rates, and short-term interest rates.