The long memory property has always played a central role in Physics since was first discovered by Hurst (1951) while studying the flow of the river Nile. Interestingly, after his seminal work, many other researchers have found the same pattern in other domains of Science such as Biology, Economics and Finance. One question that may arise when analyzing this property is the adequacy of the tests developed to detect it. Actually, empirical evidence has shown that many of these tests rely on the estimation of the Hurst exponent, for which several techniques were developed. One of the most popularized in literature is the rescaled range statistics (R/S henceforth) that has, however, shown some drawbacks since it lacks robustness in the presence of short memory and heteroskedasticity, as Mandelbrot pointed out in 1972. In the light of this, it became obvious the need for alternative approaches.

In this paper we use a different approach based on the FIGARCH (Fractional Integrated Autoregressive Conditionally Heteroskedasticity) model proposed by Baillie et al. (1996) in order to analyze the long memory behaviour of several stock markets. In particular, we compare how the long memory parameter evolves before and after the market crash of September 2008 both for developed and emerging markets. Our results show different patterns for the pre and post crisis periods revealing that the degree of long memory differs according to the level of market turbulence.

References:

[1] Hurst, H.E. (1951) Long-term storage capacity of Reservoirs, Trans. Am. Soc. Civil Eng. 116, 770-799.

[2] Baillie, R.T., T. Bollerslev and H.O. Mikkelson (1986) Fractionally integrated generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 74, 3-30.

• Legal notice:
  

  Copyright (c) Pielaszek Research, all rights reserved.
  The above materials, including auxiliary resources, are subject to Publisher's copyright and the Author(s) intellectual rights. Without limiting Author(s) rights under respective Copyright Transfer Agreement, no part of the above documents may be reproduced without the express written permission of Pielaszek Research, the Publisher. Express permission from the Author(s) is required to use the above materials for academic purposes, such as lectures or scientific presentations.
  In every case, proper references including Author(s) name(s) and URL of this webpage: https://science24.com/paper/31795 must be provided.

1.  Modelling the asymmetric behaviour of stock market volatility: New evidence