Digital transformation has made a strong presence in stock trading with the rise of digital brokerage services and platforms that support traders not only in getting a more accurate reading on the market but even trade automatically on their accounts.
|Algo-trading has become popular in areas such as foreign exchange. Photo: Shutterstock |
While trading robots now account for a significant portion of the market, algorithms and digital technology have improved trading for all.
Algorithmic trading, or algo-trading for short, is automated trading following a set of instructions to open and close trading positions on behalf of the investor. Instructions can be simple, such as buying and selling at pre-set price levels, or can be a lot more complex based on moving averages and other technical data. Some trading robots have even been programmed to monitor economic events and evaluate their potential impact on the market.
Trading robots are overwhelmingly popular in the larger bourses, with 70-80 per cent of trading volume in the US and other developed stock markets now completed through trading programmes. One of the greatest advantages of algorithmic trading is its sheer speed: decisions can be arrived at within the blink of an eye and positions opened, closed, or adjusted near-instantaneously – and definitely far ahead of the home trader masticating through the statistics and technical data on their own brainpower. This allows algo-traders to beat the general market to the punch – and there is a lot of profit in being a step ahead.
Its speed makes algo-trading widely popular in trading areas that have been almost completely mapped out and understood, like forex (especially the most popular currency pairs), where computer programmes can forecast the slightest fluctuations and scalp the market accordingly by executing trades with minuscule margins. The fact that computers can conduct far more trades within a single day than any individual trader can make them far more profitable.
Little wonder big companies and hedge funds are all working to fine-tune algorithms and shave off precious milliseconds from their execution speed – gains they are willing to pay literally millions or even billions of dollars for. While individual traders may not be able to reach the same trading efficiency and speed with their home setups, there are gains to be had for them, too.
For starters, they do not necessarily have to race with the big guns – it is enough for them to be a step ahead of the general market and that includes “manual” traders. The speed at which algorithms can parse through mind-bogglingly extensive data points while simultaneously checking on multiple market conditions can supply traders with valuable insight. For manual traders, it takes minutes or even hours to simply take in and internalise all the data at their disposal, just to make up their mind if the ticker is at a place they would consider buying in.
Apart from market analysis, algorithms also boast a myriad of tiny uses to make life easier for any trader and most brokerage platforms now offer a plethora of automated functions. A small feature of the untold utility is the notification function to keep traders updated on market developments and significant changes in their trading positions.
Called expert advisors on the MetaTrader 4 platform, any broker worth their salt provides traders access to a library of free trading bots. These bots come in a great enough variety to generally meet the needs of starters and more experienced traders alike, offering parameters of varying complexity. As they come with detailed explanations about what they do, even those without intensive technical and programming knowledge can find something that fits their trading strategy and can even use these bots as a basis for fine-tuning and tinkering.
Indeed, a good algo-trader never stops testing the validity of their algorithms, either against historical data so readily available or in demo mode for the current market. For this reason, once a trader gets more serious about algorithms, they are generally recommended not only to dive deep into the technical side of analysis but also to pick up at least the rudiments of a programming language like Python or C++ to better understand what exactly is happening.
By Tom Nguyen