Public news flow in intraday component models for trading activity and volatility

Adam Clements, Joanne Fuller () and Vasilios Papalexiou
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Joanne Fuller: QUT

No 106, NCER Working Paper Series from National Centre for Econometric Research

Abstract: Understanding the determinants of, and forecasting asset return volatility are crucial issues in many financial applications. Many earlier studies have considered the impact of trading activity and news arrivals on volatility. This paper develops a range of intraday component models for volatility and order flow that include the impact of news arrivals. Estimates of the conditional mean of order flow, taking into account news flow are included in models ofvolatility providing a superior in-sample fit. At a 1-minute frequency, it is found that first generating forecasts of order flow which are then included in forecasts of volatility leads to superior day-ahead forecasts of volatility. While including overnight news arrivals directly into models for volatility improves in-sample fit, this approach produces inferior forecasts.

Keywords: Volatility; Order flow; News; Dynamic conditional score; forecasting (search for similar items in EconPapers)
JEL-codes: C22 G00 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2015-08-26
New Economics Papers: this item is included in nep-for and nep-mst
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Persistent link: https://EconPapers.repec.org/RePEc:qut:auncer:2015_04

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