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What is FPCA for Implied Volatility Prediction about?
This document discusses the use of Functional Principal Component Analysis (FPCA) for predicting implied volatility surfaces in foreign exchange options, highlighting its advantages over traditional models like GARCH and VAR. The authors demonstrate that FPCA can effectively reduce the dimensionality of the volatility surface while maintaining accuracy, resulting in improved forecasting performance. The study concludes that using FPCA leads to lower out-of-sample prediction errors compared to standard discr
- Author
- Lujia Bai
- Language
- EN