Discuss the influence that high frequency trading algorithms have had on asset markets.
The objective of this study is to understand the rapid changes in the asset market as a result of High Frequency Trading. HFT influences various factors such as price, liquidity, welfare etc. To begin with the basic concept, an asset market is where an individual attains contractual right to a wealth that is either bought or sold. Common examples of assets are stocks, bonds, mortgages etc. The latest technological advances have revolutionized the way assets are traded. From steps one of trading; i.e. order entry to trading venue and more is now highly automated. This has dramatically reduced the costs incurred by intermediaries. Since there is a reduction in the frictions and cost of trading, this technology has the ability to enable efficient risk sharing, improve liquidity, and facilitate hedging and also to make prices more efficient. Our market consists of human and algorithmic counterparts that conduct trades based on technical analysis, fundamental analysis and pairs trading strategies. The difference between the two is the speed of trading. A high frequency trading algorithm is a program that is developed to conduct/trade large number of orders at very high speeds. The system uses complex algorithms to analyze multiple markets and execute orders based on market conditions. Firstly, the agency algorithms are the ones used by institutional traders (mutual funds etc.); mainly to split orders between markets and time to restrain their impact on prices and related risks. The aim of this was to change their long term positions at the lowest transaction cost possible. Secondly, proprietary algorithms were the ones used to take advantage of minor movements in the market. This type of trading facilitated computer power to quickly respond to arbitrage opportunities, mispricing and market signals before they are integrated into an asset market price. As insisted by Menkveld (2011), technology has dismissed the ‘monopoly’ rent. The struggle in accessing the trading data was also the prime reason for soaring transaction costs as it was a compelling entry barrier for wider variety of traders. This created a monopolistic brokerages environment. With this electronic advancement, matching and monitoring the prices became very reasonable and cheap. To explain this concept further in layman terms, the trader with the fastest speed will be making more profit than the trader with slower execution speeds.
As of 2009:
Of the 20,000 firms operating in the market today, High Frequency Trading accounts for 2% of them (in the United States). Although 2% might seem like a small representation, it accounts for 73% of all the equity trading volume now. Many HFT firms are market makers. High Frequency Trading (HFT) started becoming popular in 2007 and 2008. It became most popular when the offer to gain incentives, if the company added more liquidity to the market was made by the exchanges. Since they provide liquidity to the market, they have managed to reduce volatility and thin down bid-ask spreads. This in turn has made trading and investing cheaper for other candidates. For example, The New York Stock Exchange has a group of liquidity providers known as the Supplemental Liquidity Providers (SLPs). The SLPs adds competition and liquidity to the existing quotes on the exchange. The NYSE then pays a fee or rebate for providing liquidity as an incentive to the firm. As of 09’, the SLP rebate was 0.0015$. Multiply that by the millions of transactions that take place every day; we can confirm where a portion of the HFT profits come from.
HFT raises certain arguments; one being that HF traders have an upper hand of speed over ordinary traders which causes inequity in the markets. Researchers P.Protter and R.Jarrow justify that HFT is taking unjust advantage of their differential speed to generate “abnormal profit opportunities” to the...
References: 7. ‘A Dysfunctional Role of High Frequency Trading in Electronic Markets’, 2011, R. Jarrow, P. Protter
9. Menkveld, A., (2011), Foresight Driver Review, Electronic Trading and Market Structure
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