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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Disclaimers

U.S. Government Required Disclaimer –Futures and options trading has large potential rewards, but also large potential risk. You must be aware of the risks and be willing to accept them in order to invest in the futures and options markets. Don’t trade with money you can’t afford to lose. This website is neither a solicitation nor an offer to Buy/Sell futures or options. No representation is being made that any account will or is likely to achieve profits or losses similar to those discussed on this website. The past performance of any trading system or methodology is not necessarily indicative of future results.

CFTC RULE 4.41 – HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY, SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN.

At no time is any of the stated performance an endorsement of or a suggestion to trade. I am a trader and an educator desiring to show proof positive of trading efforts in real time. I am not a broker-dealer, nor am I a financial advisor. My trades are not to be considered an endorsement or recommendation for anyone else to trade live accounts nor do trades on my part denote or indicate that trade conditions or trade expectations are more favorable.

Hypothetical Performance Disclosure