The extreme advances in technology, computing power and artificial intelligence capabilities is affecting every industry, and stock and forex market trading are no different. Algorithmic trading is the most popular method of trading for the significant majority of traders regardless of market.
In this article we’ll explain everything you need to know about this form of trading and the different ways in which people employ the advances in trading technology.
As part of our introduction to algorithmic trading strategies, it’s important to first ensure you have a strong understanding of what algorithmic trading actually is.
Often called algo trading for short, and sometimes even black box trading, algorithmic trading is the implementation of automated trading through a computer-based and proprietary platform. It’s basically a trading strategy designed to run on “auto-pilot”, directed by pre-set instructions in the form of code.
This code tells the computer program, based on an internal algorithm, when to buy a stock or currency pair and when to sell it. The sophisticated algorithm would ideally take into account a variety of factors and analysis including:
To put it simply: everyone. Both independent retail traders and brokers make use of algorithms in their trading strategies, as well as large investment banks, mutual funds and hedge funds.
Of course, the bigger investment and financial institutions have large amounts of capital with which to invest into developing immensely sophisticated models, programs and technologies for trading headed by a team of specialists in everything from mathematics to engineering.
As will become more apparent later in this article, algo trading is particularly adept when employed in high frequency trading.
There are many, many trading strategies that are widely used and they vary hugely in many complex ways. The greatest minds and most sophisticated algorithms are constantly developing new strategies and advancing new forms of previous strategies.
The core strategies employed fall under the following four categories:
When an account is heavily invested into an index fund, think superannuation accounts and retirement funds, there always needs to be periodical periods where the fund is balanced according to the change in the underlying financial assets upon which the index is based. When this happens, or to be more technical before this happens, an algorithm is able to exploit the anticipated trades to make a profit.
This might sound easy but we’re talking mere parts of a second in time, so your average retail trader won’t have access to a platform with sophisticated enough algorithm trading capabilities to properly take advantage of this opportunity like a hedge fund could.
Similar to strategy 1, this strategy uses high frequency trades executed over the space of nanoseconds to take advantage of arbitrage between markets. For example, if a specific financial derivative is traded at a different price in different markets there is an opportunity to buy it at the lower price in market A and sell it at a higher price in market B. Simple, right? Perhaps. But easy? Definitely not. Again, the spotting of such opportunities of arbitrage and executing the trade in time to take advantage of the price difference makes it suitable primarily as an algorithmic trading strategy.
This algorithmic trading strategy uses a complex mathematical model that assumes that the price of all financial instruments will, over a specific period of time, move back to its average price historically. This process is referred to as “mean reversion”. (Mean as in the mathematical definition: average.) Highly technical indicators are used to determine moving averages and help identify average prices historically in order to trade effectively. Unlike the first two strategies, this one is more suitable for independent traders as it does not necessarily require super frequent and near-instantaneous implementation. The actual coding of the algorithm to execute the trade, however, may still require specialist knowledge and skill.
This algorithmic trading strategy is rather simple in theory: it follows the trend of prices and assumes that that momentum will continue indefinitely until there are specific signals or indicators otherwise. To a certain extent this strategy, thanks to its popularity among traders, can contribute to a short term self-fulfilling prophecy. As algorithms simultaneously zero in on a price in an upwards trend, the algorithm’s trading execution further pushes the price up quicker and sharper. The algorithm is coded to search for specific indicators or conditions according to strict parameters to determine when the trend is likely to come to the end.
As technology around artificial intelligence, or more specifically self-machine learning, is advancing in leaps and bounds, it’s revolutionising the way in which trading can be executed. Algorithms are only as good as the person who coded them. When it comes to machine learning AI, the super-sophisticated program learns automatically and updates its knowledge and ability as it goes. While not so much a trading plan itself, this strategy is focusing on a somewhat emerging form of algorithmic technology with even greater trading potential.
While there are lots of different platforms for algorithmic trading strategies, one of the more popular ones, especially for retail and independent traders, is MetaTrader 4. You don’t necessarily need to be an expert in coding either to make use of the platform, which is very appealing. Traders using MetTrader 4 enjoy access to many free and some fee-based algorithmic trading software with which you can develop and employ your own trading strategies.
Ready to find out more about the different strategies or start trading yourself with MetaTrader? Get in touch with the expert team from Global Prime today.