Understand what a trading algorithm is

The strength of algorithms is that they can automate strategies, while making operations faster and smoother without requiring human intervention.

Definition of a trading algorithm

Algorithmic trading is based on automated decision making strategies. These algorithms make it possible to get rid of human bias and make risk management foolproof. There are different types of algorithmic trading: trend following (momentum), regression, artificial intelligence (AI), text analysis (articles, social networks, etc.), arbitrage and statistical anomalies…

Unlike discretionary trading, in algorithmic trading psychological and risk management issues are by nature eliminated, since the machine is unemotional and perfectly disciplined. Indeed, if it is programmed to react to a particular scenario, it will have no qualms about executing a trade to take profits or losses. Also, since risk management is one of the major aspects of trading, a trading robot will never make a mistake in its risk calculations and will never take the initiative to increase or decrease its risk based on its emotions.

Trading graph

Some types of trading algorithms

Trend monitoring

Momentum tracking is a type of trading algorithm that consists of capturing and placing oneself in trends of varying lengths. The goal of this type of strategy is not to locate market highs and lows, but rather to ride the wave of rising and falling prices. When a market follows a very strong trend, such as during a bullrun or a bear market, this type of algorithm is very powerful and can offer high returns. On the other hand, in a low volatility market, called a range, this strategy can be subject to many false signals.

Regression

In automated trading, we also find regression systems. The goal is to identify market reversals by positioning on price levels that are considered extreme. Unlike trend following, the regression trading algorithm tries to enter positions on the highs or lows of an asset. In effect, when it believes that an asset’s price is on a high, then it will sell it, and conversely, if it believes that an asset’s price is on a low, it will buy it. This type of strategy will perform well in environments with no real trend, but will be more difficult in a strong trend.

Artificial intelligence

Trading strategies based on artificial intelligence (AI) can be varied in their subject matter: regression, trend following, anomaly, text analysis, etc. However, these strategies are difficult to master and expensive to develop, which is why they are usually reserved for investment funds. Artificial intelligence strategies are powerful but are still not very common in the crypto market.

Bot trading

Favouring trading algorithms?

Algorithmic strategies offer excellent returns while eliminating the biases that a human could have (emotions, availability, rigor, stress, fear…). Themes can be varied and thus complement each other. Indeed, each strategy performs in a particular environment. The key is therefore to diversify the strategies used in the portfolio in order to ensure robustness in the evolution of one’s capital, in any type of environment.

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