Volatility behavior of asset returns based on robust volatility ratio: Empirical analysis on global stock indices

Muneer Shaik and S. Maheswaran

Cogent Economics & Finance, 2019, vol. 7, issue 1, 1597430

Abstract: In this paper, we come up with an alternate theoretical proof for the independence and unbiased property of extreme value robust volatility estimator with respect to the standard robust volatility estimator. We show that the robust volatility ratio is unbiased both in the population and in the finite samples. We empirically test the robust volatility ratio on nine global stock indices from America, Asia Pacific and EMEA markets for the period from January 1996 to June 2017 based on daily open, high, low and close prices to understand the volatility behavior of stock returns over a period of time. Our results show that robust volatility ratio for different k-month periods is significantly less than 1 for all the global stock indices, thus finding the clear evidence of random walk behavior. This is possibly the first study based on robust volatility ratio to understand the volatility behavior of global stock indices.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/23322039.2019.1597430 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:oaefxx:v:7:y:2019:i:1:p:1597430

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/OAEF20

DOI: 10.1080/23322039.2019.1597430

Access Statistics for this article

Cogent Economics & Finance is currently edited by Steve Cook, Caroline Elliott, David McMillan, Duncan Watson and Xibin Zhang

More articles in Cogent Economics & Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().