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A GARCH analysis of dark-pool trades

Philippe de Peretti () and Oren Tapiero
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Philippe de Peretti: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique
Oren Tapiero: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: The ability to trade in dark-pools without publicly announcing trading orders, concerns regulators and market participants alike. This paper analyzes the information contribution of dark trades to the intraday volatility process. The analysis is conducted by performing a GARCH estimation framework where errors follow the generalized error distribution (GED) and two different proxies for dark trading activity are separately included in the volatility equation. Results indicate that dark trades convey important information on the intraday volatility process. Furthermore, the results highlight the superiority of the proportion of dark trades relative to the proportion of dark volume in affecting the one-step-ahead density forecast

Keywords: Dark Pools; Density Forecast; Dark Volume; Dark trade (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-for and nep-mst
Note: View the original document on HAL open archive server: https://paris1.hal.science/hal-00984834
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Published in Comment la régulation financière peut-elle sortir l'Europe de la crise ?, Ecole nationale d'administration, pp.161-182, 2014

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