Algorithmic trading refers to the use of computer algorithms to conduct trades of an individual stock or asset on an exchange or within a market. The algorithms are programmed in advance, and the computational system is given direction on when to initiate and when to conclude its trades. Most algorithmic trading is based on complex software that can be fine-tuned or honed as back testing shows its efficacy and precision. It is estimated that 88-92% of all futures emini S&P 500, NASDAQ, gold and oil are currently traded algorithmically.
What Algorithmic Trading Is
Algorithms are processes for executing sets of instructions. When applied to trading, it involves accounting for many variables, such as an asset’s price, volume and time. The algorithm solves a problem of knowing when to trade. People oversee the algorithms and can change them if hindsight testing demonstrates a problem.
The trading software takes into consideration an asset’s moving average, types of trading activities, volume of buying and selling and the asset’s price. The algorithms also take into consideration other market activities and trends, such as generalized sell-offs and market corrections.
Fast computers allow tens of thousands of trades to take place in a fraction of a second. This is particularly true with futures gold or futures NASDAQ, where price movements can be very volatile. Although algorithmic trading might seem like a new concept, it dates back to the mid-1970s. The New York Stock Exchange introduced a Designated Order Turnaround system in 1976 that made use of electronic trading systems. The emini S&P was one of the first futures indices to be traded by algorithms. Today, machine learning has honed the algorithms. The algorithms do not require as much human oversight as they used to. Algorithmic trading is used by individual investors all the way up to large trading firms.
Volume or Percentage of Algorithmic Trading
Automated trading is the future of the stock markets in the United States and around the world. What a lot of people might not realize is that the future is already here when it comes to programmed trading. Algorithms already run the things that affect your everyday life, from traffic lights to the news on your Facebook timeline. Algorithms also dominate the trading process on every stock market around the globe. Algorithmic trading systems have grown in popularity because they boost efficiency in financial markets.
In 2003, about 15% of the trades on American financial markets were triggered by algorithms. Algorithmic traders noticed that their trades went through in less time. They could access the trading platform remotely with the use of the computers and algorithms instead of having to oversee every trade themselves in real-time. The percentage of trades triggered by algorithms rose 30% by 2006. A big jump took place in 2007, around the start of the Great Recession,with 45% of trades being handled algorithmically. The rate of increase slowed to about 3-5% per year. By 2012, 85% of trades on American stock markets and exchanges were algorithmic trades.
Profitability of Algorithmic Trading
Algorithmic trading would not be so popular if it did not make a lot of money for traders. For short-term trades, the cost per trade may eat up quite a bit of profits. On the other hand, algorithmic trades allow an investor to take advantage of price changes at the microsecond level, so if the trading volume is high enough, a lot of short-term transactions can still prove to be profitable. The large-scale, institutional investors are the ones most likely to see a profit from algorithmic trading. This is because they have the technology in place to handle the high-frequency trades. They also trade at high volumes, which decreases the cost per trade.
A retail investor will have a more challenging time trying to be profitable with algorithmic trading. They might not have the same advanced algorithmic trading software or hardware in place to keep up with the big institutional traders. If they do not trade at a high volume, the costs per trade could eat up a lot or even all of their profits on a given trade. However, a retail investor who is able to craft algorithms that take advantage of the low latency should be able to carve out a profit.
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