Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/45242
Title: Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach
Authors: Dhesi, Gurjeet
Shakeel, Bilal
Ausloos, Marcel
First Published: 23-Jul-2019
Publisher: Springer (part of Springer Nature)
Citation: Annals of Operations Research, 2019
Abstract: This paper reports a new methodology and results on the forecast of the numerical value of the fat tail(s) in asset returns distributions using the irrational fractional Brownian motion model. Optimal model parameter values are obtained from fits to consecutive daily 2-year period returns of S&P500 index over [1950–2016], generating 33-time series estimations. Through an econometric model, the kurtosis of returns distributions is modelled as a function of these parameters. Subsequently an auto-regressive analysis on these parameters advances the modelling and forecasting of kurtosis and returns distributions, providing the accurate shape of returns distributions and measurement of Value at Risk.
DOI Link: 10.1007/s10479-019-03305-z
ISSN: 0254-5330
eISSN: 1572-9338
Links: https://link.springer.com/article/10.1007%2Fs10479-019-03305-z
http://hdl.handle.net/2381/45242
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, School of Management

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