Automated Analysis of News to Compute Market Sentiment: Its Impact on Liquidity and Trading

Abstract

Computer trading in financial markets is a rapidly developing field with a growing number of applications. Automated analysis of news and computation of market sentiment is a related applied research topic which impinges on the methods and models deployed in the former. In this chapter we have first explored the asset classes which are best suited for computer trading. We present in a summary form the essential aspects of market microstructure and the process of price formation as this takes place in trading. We critically analyse the role of different classes of traders and categorise alternative types of automated trading. We introduce alternative measures of liquidity which have been developed in the context of bid-ask of price quotation and explore its connection to market microstructure and trading. We review the technology and the prevalent methods for news sentiment analysis whereby qualitative textual news data is turned into market sentiment. The impact of news on liquidity and automated trading is critically examined. Finally we explore the interaction between manual and automated trading.

Keywords: Computer trading, Automated Trading, Market Sentiment, News Sentiment Analysis, News Impact, Liquidity measures, Market microstructure