Eberlein, E. and Prause, K. (2002) The Generalized Hyperbolic Model: Financial Derivatives and Risk Measures. The First World Congress of the Bachelier Finance Society, Paris, 29 June-1 July 2000, 245-267.
https://doi.org/10.1007/978-3-662-12429-1_12

has been cited by the following article:

• TITLE: Distribution Analysis of S&P 500 Financial Turbulence

  AUTHORS: Hugo Gobato Souto

  KEYWORDS: Financial Turbulence, Generalised Hyperbolic Distribution, S&P 500, Goodness-of-Fit Tests

  JOURNAL NAME: Journal of Mathematical Finance, Vol.13 No.1, February 21, 2023

  ABSTRACT: In 2010 a new financial risk measure was discovered, namely Financial Turbulence. Although it has been studied by other papers, its statistical distribution study is still missing. Knowing a financial phenomenon distribution is of importance when performing risk and portfolio management, especially when estimating parametric Value-at-Risk with Copulas and performing Monte Carlo simulations. Therefore, this paper explores the S&P 500 Fi-nancial Turbulence to determine its best distribution fit by making use of various residual measures and goodness-of-fit tests. Additionally, it makes use of in-sampling and out-sampling in the period between 01/11/2012 and 01/11/2022. The results of this research indicate that the Generalised Hyperbolic distribution describes the S&P 500 Financial Turbulence the best.