A note on the estimated GARCH coefficients from the S&P1500 universe

Georgios Bampinas (), Konstantinos Ladopoulos () and Theodore Panagiotidis
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Konstantinos Ladopoulos: Citrix Systems Research & Development Ltd, UK

Working Paper series from Rimini Centre for Economic Analysis

Abstract: We employ 1440 stocks listed in the S&P Composite 1500 Index of the NYSE. Three benchmark GARCH models are estimated for the returns of each individual stock under three alternative distributions (Normal, t and GED). We provide summary statistics for all the GARCH coefficients derived from 11520 regressions. The EGARCH model with GED errors emerges as the preferred choice for the individual stocks in the S&P 1500 universe when non-negativity and stationarity constraints in the conditional variance are imposed. 57% of the constraint’s violations are taking place in the S&P small cap stocks.

Keywords: GARCH; GJR-GARCH; EGARCH; alternative distributions; volatility; time-series (search for similar items in EconPapers)
Date: 2017-04
New Economics Papers: this item is included in nep-cba, nep-ecm and nep-eec
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Citations: View citations in EconPapers (1)

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http://www.rcea.org/RePEc/pdf/wp17-09.pdf

Related works:
Journal Article: A note on the estimated GARCH coefficients from the S&P1500 universe (2018)
Working Paper: A note on the estimated GARCH coefficients from the S&P1500 universe (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:17-09

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