Forecasting daily return densities from intraday data:
a multifractal approach
Forecasting daily return densities from intraday data:
a multifractal approach
This paper proposes a new approach for estimating and forecasting the moments and probability density function of daily financial returns from intraday data. This is achieved through a new application of the distributional scaling laws for the class of multifractal processes. Density forecasts from the new multifractal approach are typically found to provide substantial improvements in predictive ability over existing forecasting methods for the EUR/USD exchange rate, and are also competitive with existing methods when forecasting the daily return density of the S&P500 and NASDAQ-100 equity index.
863-881
Hallam, M.
90b75cfc-3890-4567-be1a-075069235129
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e
October 2014
Hallam, M.
90b75cfc-3890-4567-be1a-075069235129
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e
Hallam, M. and Olmo, J.
(2014)
Forecasting daily return densities from intraday data:
a multifractal approach.
International Journal of Forecasting, 30 (4), .
(doi:10.1016/j.ijforecast.2014.01.007).
Abstract
This paper proposes a new approach for estimating and forecasting the moments and probability density function of daily financial returns from intraday data. This is achieved through a new application of the distributional scaling laws for the class of multifractal processes. Density forecasts from the new multifractal approach are typically found to provide substantial improvements in predictive ability over existing forecasting methods for the EUR/USD exchange rate, and are also competitive with existing methods when forecasting the daily return density of the S&P500 and NASDAQ-100 equity index.
Text
Hallam_Olmo_IJoF.pdf
- Accepted Manuscript
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e-pub ahead of print date: 20 June 2014
Published date: October 2014
Organisations:
Economics
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Local EPrints ID: 369374
URI: http://eprints.soton.ac.uk/id/eprint/369374
ISSN: 0169-2070
PURE UUID: ff5db4b6-57b5-4d6e-8f7d-59a187f0613c
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Date deposited: 02 Oct 2014 11:04
Last modified: 15 Mar 2024 03:46
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Author:
M. Hallam
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