Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach

Journal article


Dhesi, G., Shakeel, B. and Ausloos, M. (2019). Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach. Annals of Operations Research. pp. 1-4. https://doi.org/10.1007/s10479-019-03305-z
AuthorsDhesi, G., Shakeel, B. and Ausloos, M.
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.

Year2019
JournalAnnals of Operations Research
Journal citationpp. 1-4
PublisherSpringer
ISSN0254-5330
Digital Object Identifier (DOI)https://doi.org/10.1007/s10479-019-03305-z
Publication dates
Online23 Jul 2019
Publication process dates
Accepted10 Jul 2019
Deposited29 Aug 2019
Accepted author manuscript
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Open
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https://openresearch.lsbu.ac.uk/item/87yyq

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