Artikel

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

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.

Sprache
Englisch

Erschienen in
Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 7 ; Year: 2019 ; Issue: 1 ; Pages: 1-27 ; Abingdon: Taylor & Francis

Klassifikation
Wirtschaft
Model Construction and Estimation
Financial Econometrics
Hypothesis Testing: General
International Financial Markets
Thema
volatility modeling
robust estimation
extreme value estimators
Brownian motion
volatility ratio

Ereignis
Geistige Schöpfung
(wer)
Shaik, Muneer
Maheswaran, S.
Ereignis
Veröffentlichung
(wer)
Taylor & Francis
(wo)
Abingdon
(wann)
2019

DOI
doi:10.1080/23322039.2019.1597430
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Shaik, Muneer
  • Maheswaran, S.
  • Taylor & Francis

Entstanden

  • 2019

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