Forecasting Realized Volatility Using Neural Networks
|Author:||Mgr. Jindřich Jurkovič|
|Year:||2013 - summer|
|Leaders:|| doc. PhDr. Jozef Baruník Ph.D.
|Work type:|| Finance, Financial Markets and Banking
|Awards and prizes:|
|Abstract:||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.