High-frequency trading has gained much attention following Michael Lewis’s 2014 book “Flash Boys.” Many stock markets in advanced countries have moved from classic or traditional trading. Trading is now fast-paced, and African Stock markets-Stock Exchanges which are heavily classical, must adapt and improve their stock trading.
High-Frequency Trading (HFT) refers to applying algorithms in shares trading at high speed to send the shares into the markets at a relatively high rate. The fact is well elaborated in the High-frequency Trade Dummies and the Dark pools written by Jay Vaananen in 2015. Moreover, the application of complicated algorithms in analyzing markets and dividing players into two camps has caused a distortion as to how Traditional methods of Trading used to occur.
Wall Streeters who support HFT think that the stock market has benefitted them, but the second Wall Street camp says the contrary. Thousands of trades are executed within milliseconds after they have been sent out. HFT is powered by fast algorithms that attempt to detect minute price variations in stocks, which might be as little as a penny or a fraction of a penny. When you do this a thousand times a day, these fractions of—pennies—add up to a lot of money.
Orders have traditionally been put in price/time priority, which means that the best price is always first in line—the lowest possible price for the buyer and the highest possible price for the seller. For orders of the same price, the demands that arrived first are placed first in the queue.
HFT has allowed market participants to bypass the wait by placing specific orders on particular exchanges in this arena. HFT has prioritized the importance of news and information. In the hands of an HF trader, the impact of breaking news on market pricing and price movement is breathtaking and advantageous.
Opponents of HFT think a winner-takes-all race has been created – with the first one to make the trade on the news being the one who takes all the profits. HFT has brought speed into the financial market. It is undeniable that HFT has brought down the cost of investing and trading in the markets and helping to provide liquidity, making the market a better, well-oiled machine.
Some people have stated their opposition to HFT, claiming that it gives an unfair advantage to some people by engaging in predatory behavior and exploiting other investors. HFT, according to the argument, is equivalent to a manipulated market and should be prohibited. Trading at high speeds should be permitted. Due to the use of mathematical models and algorithms, HFT has replaced many broker-dealers in making decisions, removing the need for human interaction and decision-making. Microsecond decision-making can cause the market to react irrationally.
According to a report by Bloomberg on May 6, 2010 (Sec.gov) the Dow Jones Industrial Average (DJIA) dropped 1,000 points and 10 percent in just 20 minutes before rebounding. According to a government investigation, the crash was sparked by a large order that caused a sell-off. High-frequency trading (HFT) enables major firms to benefit at the expense of institutional and retail investors. Also, HFT is criticized for providing “ghost liquidity,” meaning that the liquidity it supplies is available one second and gone the next, making trading difficult. Not to mention the fact that HFT grew in popularity as a result of financial market flaws. Regulators and legislators have the responsibility of establishing the regulations that govern HFT. For this to happen, Africa requires solid financial market regulations and procedures.
Our market landscape has changed over time, with technological advancements far outpacing regulatory adjustments. Regulators on the stock exchanges of sophisticated countries are just now scouring the market for operators they suspect of manipulating the market and exploiting investors. It is a reflection of the regulators’ deficiencies—Man versus Machine. Regulators have little or no tools or experience to deal with what is going on in the market because of the speed at which these HFT agreements are completed. Legislation, in my opinion, may take the pleasure out of the market. Some HFT players may need to slow down to keep up.
Ken is a Quantitative Trader with experience in investments, quantitative finance, financial modelling and algorithmic trading in Global Investable Markets (GIM). He enjoys using Bayesian Statistics, Time Series and Machine Learning in developing Robust consistent Alphas in Equities Market, FX, ETPs and Derivatives instruments. He enjoys deep dives in understanding High Frequency Trading infrastructures and improving how the African financial markets work. He holds a Bachelor's in Actuarial Science from Strathmore Institute of Mathematical Sciences : An Executive Program in Algorithmic Trading (EPAT) certificate in Algo Trading from QuantInsti : A current MSc student in Financial Engineering at World Quant University.