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Non-Linear Volatility Modelling of Economic and Financial Time Series Using High Frequency Data
Citation
Matei, M, Non-Linear Volatility Modelling of Economic and Financial Time Series Using High Frequency Data, Romanian Journal of Economic Forecasting, 14, (2) pp. 116-141. ISSN 1582-6163 (2011) [Refereed Article]
Copyright Statement
Copyright 2011 Institute for Economic Forecasting
Official URL: http://www.ipe.ro/rjef.htm
Abstract
The current work undertakes an overview of the forecasting volatility with high
frequency data topic, attempting to answer to the fundamental latency problem of
return volatility. It surveys the most relevant aspects of the volatility topic, suggesting
advantages and disadvantages of each alternative in modeling. It reviews the concept
of realized volatility and explains why forecasting of volatility is more effective when
the model contains a measure of intraday data. A discrete and a continuous time
model are defined. Sampling methods at different frequencies are reviewed, and the
impact of microstructure noise is considered. Details on procedures employed in the
literature with respect to modeling and forecasting using realized models are
discussed, while an empirical exercise will prove the advantages of using measures of
high frequency data.
Item Details
Item Type: | Refereed Article |
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Keywords: | High frequency, Volatility, Modeling, Forecasting, Realized measures, Microstructure noise |
Research Division: | Commerce, Management, Tourism and Services |
Research Group: | Banking, finance and investment |
Research Field: | Financial econometrics |
Objective Division: | Economic Framework |
Objective Group: | Measurement standards and calibration services |
Objective Field: | Measurement standards and calibration services not elsewhere classified |
UTAS Author: | Matei, M (Dr Marius Matei) |
ID Code: | 99869 |
Year Published: | 2011 |
Web of Science® Times Cited: | 1 |
Deposited By: | Economics and Finance |
Deposited On: | 2015-04-14 |
Last Modified: | 2015-05-11 |
Downloads: | 0 |
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