Algorithmic Trading Strategy: definition and how that work

The Algorithmic Trading is an automated system where computers make trading decisions based on algebraic equations describing the price action with numbers and formulas.

While observing the financial markets and the price action during a certain period, Forex traders could have noticed that the price action has repetitive conditions or cycles with the same performance. What’s more, the technical analysis and indicators could have similar patterns and signals, describing the price action in numbers. Trading signals, reversal conditions, breakouts, and accelerations come in line with certain parameters, which might be used to create a forex algorithm trading based on the if-then statement. This market’s feature is used in the creation of trading systems and strategies based on technical indicators.

With the technology revolution and the growing role of artificial intelligence in our everyday life, computers start to displace people from many professions. Computerized systems are also getting more and more popular in Forex trading because the machine, with a proper learning and precise algorithm, can deliver much more accurate results, execution speed and higher efficiency than human traders.

Computerization of the order flow in financial markets began in the early 1970s, with some landmarks being the introduction of the New York Stock Exchange’s “designated order turnaround” system (DOT, and later SuperDOT), which routed orders electronically to the proper trading post, which executed them manually.

What is Algorithmic Trading Software?

Forex algorithmic trading software can describe the current market situation, determine the trend’s direction and identify support and resistance levels.

A set of such codes is used to create the best algorithmic trading software which can buy or sell financial assets without humans intervention. Any trader can program an algorithm of trading decisions, backtest it on the past performance, turn the software on to trade automatically and focus on something else instead of sitting in front of the trading terminal throughout days and weeks.

Technical parameters to describe the market conditions

Every technical indicator has several parameters describing the current market situation. For instance, the volatility of an asset can be measured by standard deviation used in Bollinger Bands indicator, rate spikes might be compared to the average true range included in the Average Directional Index formula, relation between average gain to average loss points to the strength of a trend reflected by Relative Strength Index and so on. A step-by-step calculation of those parameters creates a base for equations to formulate conditions to buy or sell a currency pair, stock, commodity or cryptocurrency. Trading algorithms consist of a set of those if-then equations.

For example, the simplest condition to enter the market might be shown as a comparison of the current price with the moving average value. If the rate becomes higher than the MA after being lower, then it’s time to buy an asset. And if the rate breaks through the MA from above, then short positions should be opened.

Additional factors used in if-then equations for algorithms

Besides the usual technical indicators, several additional factors could be analysed in terms of making trading decisions. Trading volume has an impact on volatility, enlarging the range of the price, overbought and oversold conditions influence the assets’ behaviour, sharp whipsaws and long shadows on candlesticks reflect strong resistance/support levels, etc. The algorithm could include multi-level conditioning in terms of trading decisions and profitable entries with a low number of false signals. Complicated calculations are tough for human traders, while automated trading systems can provide a large volume of computing much faster and easier.

How does Forex Algorithmic Trading Work?

The steps described above represent the Quantitative Analysis or Modeling thus a trader keen on developing algorithmic trading strategies has to obtain a certain experience in the technical analysis including the knowledge of mathematical formulas of technical indicators and their programming codes. Besides that, the creator of an automated system has to have great skills in coding using different programming languages. The most popular types of coding languages are Python, Mathlab, Perl, C++ and Java. MetaQuotes Corporation – the owner and developer of the most widely-used trading platform MetaTrader5 – have developed an own coding language MQL4 to interact with the terminal directly, creating Automated Expert Advisors and trading algorithms. Forex traders can develop do-it-yourself algorithms or purchase an existing solution connected to a terminal.

Here is a list of elements and steps required to create an automated trading system:

  • A trading idea based on technical indicators’ rules and combinations;
  • Quantitative analysis and modelling skills;
  • Programming skills and knowledge of different coding languages;
  • Historical quotes data to backtest a strategy;
  • Hardware and collocation facility to provide a fast connection to brokerage servers.

Advantages and Disadvantages of Algorithmic Trading System

Algorithmic trading software is able to open and close more deals than a human trader due to the speed of analysis and calculation. Software is free of emotional impact, which often leads to mistakes and wrong decisions by humans. Execution speed, the volume of computed and analyzed data and the overall efficiency of trading decisions make algo trading much more profitable and reliable than manual trading, especially when it comes to scalping strategies. At the same time, if fundamental conditions change, having a strong impact on the market’s sentiment, technical indicators might increase the number of false trading signals, forcing traders to adapt trading algorithms to a different environment.

More information on FinmaxFX.

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