Work detail

Forecasting Realized Volatility Using Neural Networks

Author: Mgr. Jindřich Jurkovič
Year: 2013 - summer
Leaders: doc. PhDr. Jozef Baruník Ph.D.
Consultants:
Work type: Finance, Financial Markets and Banking
Masters
Language: English
Pages: 77
Awards and prizes:
Link:
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.

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