Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach
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.
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Open access
Citation : 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.1-14.
ISSN : 0254-5330
Research Institute : Finance and Banking Research Group (FiBRe)