A High Frequency Trading Explanation and Understanding Automated Algorithmic Trading

A High Frequency Trading Explanation and Understanding Automated Algorithmic Trading
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The use of computers by investment banks, hedge funds, and other institutional investors has been around for decades and the acceleration they give to transactions and fluctuations on the exchanges gives rise to some interesting scenarios at time. As more powerful computers evolve, so does their use for generating trading profits. One of the latest developments of this is known as high frequency trading (HFT). Many investors don’t know what it is and need a high frequency trading explanation.

High Frequency Trading (HFT)

High frequency trading (HFT) is a form of quantitative trading that began when exchanges started offering incentives to companies in an effort to increase liquidity and competition for existing quotes. A typical fee or rebate would be $0.0015 per transaction. These incentives on top of favorable spreads can be a good chunk of change when millions of transactions per day are executed by one company’s computer.

HFT is typically used by large institutional investors. Powerful computers are utilized with trading platforms that are programmed with complex algorithms to execute trades at extremely high speeds based on existing market conditions. These execution speeds can be a matter of milliseconds, 3,000 trades per second for many, to take advantage of small differences in share prices, and are capable of spanning trading venues. For trading, as in business in general, it’s all about increasing the bottom line. The fastest computers bring in the highest profits.

HFT and Algorithmic Trading

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HFT is also used to implement algorithmic trading. Understanding automated algorithmic trading is helpful when reading about the issues surrounding HFT.

Algorithmic trading is a technique used by large institutions for purchasing large amounts of stocks. The idea behind this for a single stock is to purchase a large block without creating large disparities in its market price. In order to do this, powerful computers are programmed with highly complex mathematical models to determine emerging trends and optimal times to buy or sell stocks. Large blocks are divided into many smaller blocks and they will be bought or sold this way.

HFT allows this process to be performed at dazzlingly fast speeds. Being able to detect small shifts in market prices quickly also helps traders beat the trends to the marketplace which makes smaller spreads possible resulting in favorable returns and significant profits.

Issues Regarding HFT

There are issues that anyone seeking a high frequency trading explanation should also be made aware of.

Is HFT Unethical?

The large institutions are able to get information faster than the rest of the public. This seems unfair to smaller institutions and investors who don’t have the advantage of fast programs on powerful computers.

Unexpected Program Behavior

If a program behaves in an unexpected way, what can happen to other programs and investors?

A good example of this is the notorious “Flash Crash” on May 6, 2010. At 2:30 pm EST there was a quick drop and recovery in stock market prices that triggered 21,000 trades, probably from other programs, that had to be canceled by the securities exchanges. Whatever the cause happened to be, some mention a single stub order, it seems that a computer program might not have had all of the possibilities covered for securities trading.

Liquidity

One of the favorable arguments for HFT is that it adds liquidity to the markets, that is, it adds to the level of trading activity, which in turn stabilizes prices. The other side of this mentions that the traders aren’t required to provide this, so it’s unlikely that they won’t be providing liquidity when the market needs it.

For anyone looking for a high frequency trading explanation, this is one of the more recent techniques being used by investment banks, hedge funds, and other institutional investors. It was estimated that in 2009 HFT accounted for 50% of the orders on exchanges. It’s easy because a computer’s doing all the work. It’s profitable; no one will deny that. But there are issues concerning it’s fairness and program behavior among others. These have been enough for the Securities and Exchange Commission (SEC) and other organizations to be scrutinizing and considering possible regulatory measures.

References

Undisclosed, “Flash Crash,” Dictionary, 2010. Investopedia. Retrieved October 17, 2010 from the World Wide Web: https://www.investopedia.com/terms/f/flash-crash.asp

Undisclosed, “High-Frequency Trading - HFT,” Dictionary, 2010. Investopedia. Retrieved October 17, 2010 from the World Wide Web: https://www.investopedia.com/terms/h/high-frequency-trading.asp

Undisclosed, “Quantitative Trading,"Dictionary, 2010. Investopedia. Retrieved October 17, 2010 from the World Wide Web: https://www.investopedia.com/terms/q/quantitative-trading.asp

SEC, “Concept Release: Concept Release on Equity Market Structure; Proposed Rule”, Securities and Exhcange Commission, January 14, 2010. Retrieved October 17, 2010 from the World Wide Web: https://www.sec.gov/rules/concept/2010/34-61358.pdf

SEC, “SEC Issues Concept Release Seeking Comment on Structure of Equity Markets,” Securities and Exchange Commission, January 13, 2010. Retrieved October 17, 2010 from the World Wide Web: https://www.sec.gov/news/press/2010/2010-8.htm

Nandini Sukumar, “High-Frequency Trading Needs More Oversight, EU Commissioner Barnier Says,” Bloomberg, Oct.12, 2010. Retrieved from the World Wide Web: https://www.bloomberg.com/news/2010-10-12/high-frequency-trading-needs-more-oversight-eu-commissioner-barnier-says.html