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Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data

Arnerić, Josip

,

Tea Poklepović

Poklepović, Tea

and

Jul 28, 2018

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Business Systems Research Journal

Volume 9 (2018): Issue 2 (July 2018)

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Published Online: Jul 28, 2018

Page range: 18 - 34

Received: Jan 29, 2018

Accepted: Apr 21, 2018

DOI: https://doi.org/10.2478/bsrj-2018-0016

Keywords
high-frequency data, realized variance, nonlinearity, long memory, jumps, leverage, feedforward neural networks, Heterogeneous AutoRegressive model

© 2018 Josip Arnerić, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Arnerić, Josip

Faculty of Economics and Business, University of Zagreb,Zagreb, Croatia

Poklepović, Tea

Faculty of Economics, Business and Tourism, University ofSplit, Croatia

Teai, Juin Wen

National University ofSingapore, Singapore

Language:: English

Publication timeframe:: 2 times per year
Journal Subjects:: Business and Economics, Business Management, Management, Organization, Corporate Governance, Business Management, other, Mathematics and Statistics for Economists, Mathematics

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