Demystifying algorithmic trading in cryptocurrency markets

The following article is an op-ed written by Laurent Benayoun, CEO of Acheron Trading.

Algorithmic trading, or “algorithmic trading,” has quickly established itself in the financial landscape, especially in the volatile and high-paced cryptocurrency market. While it is often seen as the domain of high-frequency traders with deep pockets, algorithmic trading is, at its core, about automating trading strategies to create a more systematic and unbiased approach. The cryptocurrency market has proven to be an ideal playground for these strategies, due to its 24/7 operation, high volatility, and rapid development, but misconceptions persist.

While many assume that automated trading is synonymous with high-frequency trading (HFT), it is actually a broader category. In fact, algorithmic trading is responsible for this About 60-70% of the total trading volume In developed markets, with a large portion of automated trades replacing human inconsistencies with disciplined, data-backed decisions. The algorithm may follow simple rules, such as moving averages for crossovers, or more advanced predictive models, strategies that provide precision and structure to trading decisions in a market that never stops.

Despite its strengths, algorithmic trading faces challenges: the biggest of which is the need to adapt to unexpected market shifts and rapidly changing technologies. However, its potential is enormous: the size of the global algorithmic trading market has been estimated at approx $17 billion in 2023 and is expected to reach $65.2 billion by 2032and is growing steadily as both individual players and enterprises adopt these technologies. This growth demonstrates the potential for automated trading to facilitate faster, more data-informed trades, while democratizing access to trading strategies previously reserved for institutional players. By addressing these challenges and dispelling myths, we see how algorithmic trading is transforming cryptocurrencies into a more accessible and flexible landscape for all types of traders.

Algo trading is not just for big players

One common misconception is that algorithmic trading requires significant infrastructure and data resources, making it exclusive to those with deep pockets. While high-frequency trading can indeed benefit from cutting-edge technology, most algorithmic strategies can be implemented using basic tools. Many algorithms today do not focus on speed, but rather on simple functions like dollar cost averaging strategy rather than gaining a split-second advantage.

Dispelling the myth that algorithmic trading is limited to the extreme elite is crucial in expanding access to these strategies for all traders. This is especially true for cryptocurrencies, where algorithmic trading accounts for up to… 80% of the daily trading volume on some major stock exchangesMaking it an effective tool for interpreting and responding to real-time shifts unique to this market.

In the cryptocurrency space, for example, we see clear impacts from influential voices, whether it’s Elon Musk’s tweet about Dogecoin or regulatory announcements that send shockwaves through the market. Some traders use natural language processing (NLP) to record sentiment in social media posts and newspaper articles, and evaluate whether a statement is positive or negative. By doing this, algorithms can react faster than any human, and take positions consistent with expected market sentiment. But although these models can be incredibly powerful, they must be used with caution, because their reliance on the “crowd” can sometimes amplify irrational market movements.

Furthermore, using machine learning, algorithms can be trained to identify market patterns, which can then inform trade decisions. But machine learning is not a “set and forget” solution. It requires constant improvement and adaptation, especially in a market as dynamic as cryptocurrencies.

There is no doubt that algorithmic trading has clear advantages over manual trading in terms of speed, scalability and consistency. The algorithms don’t get tired, aren’t affected by emotions, and can execute trades 24/7, which are invaluable traits in the fast-paced world of cryptocurrencies. However, manual trading still holds an important place, especially in long-term strategies or scenarios that require human judgment and flexibility.

There is a common myth that algorithms will always outperform manual trading, but this is not the case. Rather than replacing traditional methods, algorithmic trading works best as a complement to them, blending the efficiency of automation with the insight of human experience.

Institutional tools for all traders

One of the most exciting developments in the field of algorithmic trading is the increasing accessibility of tools such as Neuro-Linguistic Programming (NLP) and Machine Learning (ML). Today, even relatively simple strategies, such as setting up an automatic buy order when a particular asset reaches a predetermined price threshold, can be implemented with minimal programming knowledge.

This democratization allows retailers to participate with tools previously reserved for large institutions, promoting a more level playing field and enabling a broader range of market participants to compete and implement their own strategies.

As the cryptocurrency market continues to mature, algorithmic strategies must evolve alongside. Trends like meme currencies require flexibility from algorithmic traders. New regulatory frameworks, such as MiCA in Europe, add further complexity, as compliance and market adaptability become increasingly essential. Innovations such as new decentralized exchange mechanisms are also likely to influence trading methods moving forward.

A more flexible market with Algo Trading

Ultimately, automated trading contributes to building a more flexible market, where information is integrated into prices more efficiently and trading decisions are more systematic. Retail access to these tools also fosters a diverse market.

Going forward, responsible algorithmic trading can drive growth and resilience across digital asset markets, making cryptocurrencies the future of finance.