Analysing the implications of algorithmic high frequency trading on the bid-ask spread in commodity markets

Abstract

The rapid development in Informational Technology throughout the years, without a doubt has left a significant impact on the financial sector. This rapid development led the financial industry to shift from manual based processes, where traders engage in open outcry trading at a stock exchange, to one where trades are executed using a computer based trading system. This shift in technology has given rise to what is better known as Algorithmic High Frequency Trading. The aim of this report and research is to analyse whether the introduction of Algorithmic High Frequency Trading and pre-determined mathematical models has left an impact on the Bid-Ask Spread of Commodities, which is essentially the difference between the highest price at which a buyer is willing to pay for the underlying security, and the lowest price a seller is willing to accept. In order to conduct the above described analysis, an econometric model was formulated to specify the statistical relationship between the Bid-Ask Spread and its main determinants, namely; Price of the security, Volume, and Volatility. In order to analyse and test the econometric model, an empirical analysis was undertaken by utilising a number of quantitative statistical measures. The quantitative statistical measures will allow one to obtain and be able to observe and analyse the relationship and behaviour of the main determinants of the Bid-Ask Spread.