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

Date

2019-07-23

Advisors

Journal Title

Journal ISSN

ISSN

0254-5330

Volume Title

Publisher

Springer

Type

Article

Peer reviewed

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.

Description

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

Keywords

Financial forecasting and simulation, Asset pricing, Simulation modelling, Financial econometrics

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.

Rights

Research Institute

Finance and Banking Research Group (FiBRe)