Impact of News on Asset Behaviour: Return, Volatility and Liquidity in an Intra-Day Setting
33 Pages Posted: 23 Jul 2013 Last revised: 19 Nov 2013
Date Written: July 22, 2013
We report an empirical study of a predictive analysis model for equities; the model uses high frequency (minute-bar) market data and quantified news sentiment data. The purpose of the study is to identify a predictive model which can be used in designing automated trading strategies. Given that trading strategies take into consideration three important characteristics of an asset, namely, return, volatility and liquidity, our model is designed to predict these three parameters for a collection of assets. The minute-bar market data as well as intraday news sentiment metadata have been provided by Thomson Reuters.
Keywords: News sentiment, high frequency data, return, volatility, liquidity, predictive analysis
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