Algorithmic trading is a method of executing a large order using automated pre-programmed systems. The use of algorithmic trading grew in popularity in the early 2000s when there was an increased use of electronic communication networks (ECNs) and spread-betting services, which allowed traders to issue orders quickly and easily. Algorithmic trading, also known as black-box trading, algo trading, or automated trading, relies on a computer program that in turn uses a specific set of instructions to place a trade. In theory, the trade can generate profits much faster than a human trader can. In essence, it comes down to the use of strategy, and just as there exists gaming strategies, there also exist strategies for the game of money…
Why algo trading can be advantageous
- The ability to predict shares and stock prices are better.
- The placement of a trade or trades is immediate and exact.
- The timing of the trade is more accurate and instant, and this can help to evade any major price alterations.
- Transaction costs can be lessened.
- Multiple market conditions can be monitored and traded on.
- Margins for manual errors can be drastically reduced.
- Tests can be performed based on historical and real-time data in order to ascertain if a trading strategy is viable.
- Removes a large segment of psychological or emotional involvement.
Algorithmic trading strategies
The most common and easiest to implement strategies are trend-following strategies, and these include channel breakouts, moving averages, technical indicators and price level movements. These strategies are easy to implement by way of algo trading because they don’t require predictions or forecasts. Quite simply put, trades are made based on the instances of appealing trends. There are no complexities when using algorithmic trading on trends as the ‘bot’ simply mimics what it sees as desirable.
Trading range (mean reversion)
This strategy is a particularly interesting one because it assumes that the movement of an asset is a one-time and rare opportunity. To further elaborate, it works on the principle that the high and low prices of an asset is an anomaly bound to revert to its mean value (average value). The algorithm, once implemented, will automatically place a trade once the price of an asset suddenly jumps out its typical range.
What are the technical requirements?
Algorithmic trading, or automated trading is a programme which in order to create, requires both coding skills and trading skills. Because algo trading is reliant on a trading strategy, the strategy itself must be uncomplicated to the best of its ability so that it can be programmable. Should the strategy be one of a complex nature, then it will be harder to programme. Algorithmic trading software is not the exclusive domain of a trader who has a good command of coding, it can be bought. However, if bought, then the trader purchasing the software must accept that the programme is based on the knowledge of someone else. In addition, like most if not all software applications, regular updates are required to coincide with the constant changes in the market conditions. As such, algorithmic software must be updated accordingly, and if not done so by a skilled programmer or broker company, then it won’t serve in an effective capacity for too long. The technical requirements of algorithmic trading are as follows:
- Adequate algorithmic programming knowledge to program the selected strategy, a hired and knowledgeable programmer, or a pre-made automated program (which can usually be purchased).
- Solid network connectivity and a reputable trading platform from a regulated broker.
- Access to applicable market data that can be constantly monitored by the automated software for profitable possibilities.
- The required software infrastructure that allows backtesting to be done as to verify the validity of a strategy before taking it live.
- Access to historical data for backtesting.