Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/245218 
Year of Publication: 
2019
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 7 [Issue:] 1 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2019 [Pages:] 1-27
Publisher: 
Taylor & Francis, Abingdon
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 as proposed in the paper by Muneer & Maheswaran (2018b). We show that the robust volatility ratio is unbiased both in the population as well as in finite samples. We empirically test the robust volatility ratio on 9 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.
Subjects: 
volatility modeling
robust estimation
extreme value estimators
Brownian motion
volatility ratio
JEL: 
C51
C58
C12
G15
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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