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The Handbook of News Analytics in Finance by Leela Mitra, Gautam Mitra

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11.2 WHAT CAUSES VOLATILITY ASYMMETRY?

Increased volatility while market prices drop is referred to as volatility asymmetry. The current section summarizes some of the results of Talpsepp and Rieger (2009) on measuring and empirically investigating various causes of volatility asymmetry.

11.2.1 Measuring volatility asymmetry

There are a number of approaches to measuring volatility asymmetry. We can derive the asymmetry from different types of volatility estimation models. A direct approach compares volatility of up and down markets (which has its drawback when linking different market periods to corresponding volatility). We favored using more of an ad hoc model that already incorporates the asymmetry estimation in its original setup. The choice also depended on data availability and an exact research focus.

Although the current literature on volatility (see, e.g., Andersen, Bollerslev, and Diebold, 2003) has shifted to using realized volatility from intraday returns, such data are not available for all markets and longer time periods. As we study a wide range of markets for a long time period, we use the asymmetric power GARCH (APARCH) model of Ding, Granger, and Engle (1993) with asymmetric t-distribution. There is a wide choice of GARCH-type models (see, e.g., Poon and Granger, 2003) that could be used for the task when using daily returns. But as the APARCH model contains an asymmetry parameter it is one of the most natural choices for this task. Additionally, APARCH proved ...

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