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Forecasting Realized Volatility Using Neural Networks
Jurkovič, Jindřich ; Baruník, Jozef (advisor) ; Krištoufek, Ladislav (referee)
In this work, neural networks are used to forecast daily Realized Volatility of the EUR/USD, GBP/USD and USD/CHF currency pairs time series. Their performan-ce is benchmarked against nowadays popular Hetero-genous Autoregressive model of Realized Volatility (HAR) and traditional ARIMA models. As a by-product of our research, we introduce a simple yet effective enhancement to HAR model, naming the new model HARD extension. Forecasting performance tests of HARD model are conducted as well, promoting it to become a reference benchmark for neural networks and ARIMA.

See also: similar author names
1 Jurkovič, Jan
4 Jurkovič, Juraj
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