Volatility estimators based on high-frequency information from the share capitalization index (Colcap) in Colombia
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Abstract
The purpose of the article was to determine the behavior of the volatility of the Capitalization Index of the Colombian Stock Exchange (Colcap), in the period from January 17th, 2008 to April 30th, 2020. For the development of this work, the study employed the autoregressive conditional heteroscedasticity models proposed by Engle (1982) and Bollersev (1986), and the Egarch extension proposed by Nelson (1991) due to its wide application in researches that seek to determine the underlying risks in financial time series. The results suggest that the use of the GARCH (1,1) and Egarch (1,1) specifications are the most efficient to capture sudden changes in the volatility of the returns of the index, which becomes more noticeable in periods with the presence of External shocks such as the 2008 financial crisis, the oil price war and more recently the COVID-19 pandemic, causing higher levels of risk and uncertainty for investors. The Egarch extension has a positive skew coefficient for the present study, which means that unexpected announcements do not generate drastic changes in the variance of the returns.
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