The following article is an opinion piece by Laurent Benayoun, CEO of Acheron Trading
Algorithmic trading, or ‘algo trading’, has quickly established itself in the financial landscape, especially within the volatile, fast-paced crypto market. While algo trading is often seen as a domain for high-frequency traders with deep pockets, at its core it is about automating trading strategies to create a more systematic, unbiased approach. The crypto market has proven to be an ideal playground for these strategies given its 24/7 operation, high volatility and rapid evolution, but misconceptions remain.
Although many assume that algo trading is synonymous with high-frequency trading (HFT), it is actually a broader category. In fact, algorithmic trading is responsible for this approximately 60-70% of the total trading volume in developed markets, where a significant portion of transactions are automated to replace human inconsistencies with disciplined, data-driven decisions. An algorithm can follow simple rules such as moving average crossovers or more advanced predictive models, strategies that bring precision and structure to trading decisions in a market that never stops.
Despite its strengths, algorithmic trading faces challenges: the biggest is the need to adapt to unpredictable market shifts and rapidly changing technologies. However, its potential is enormous: the size of the global algorithmic trading market was estimated at approx $17 billion in 2023 and expected to reach $65.2 billion by 2032which is steadily growing as both retail and institutional players adopt these technologies. This growth demonstrates algo trading’s potential to enable faster, more data-driven trades while democratizing access to trading strategies previously reserved for institutional players. By addressing these challenges and dispelling myths, we see how algo trading is transforming crypto into a more accessible and resilient landscape for all types of traders.
Algo Trading is not just for big players
A common misconception is that algo trading requires substantial infrastructure and data resources, making it exclusive to those with deep pockets. While high-frequency trading can indeed benefit from cutting-edge technology, most algo strategies can be implemented with basic tools. Many algorithms today don’t focus on speed, but on simple functions like dollar-cost averaging strategy, rather than gaining a split-second advantage.
Dispelling the myth that algo trading is limited to the ultra-elite is critical to increasing access to these strategies for all traders. This is especially true in crypto, where algorithmic trading accounts for maximum 80% of daily trading volume on some major exchangesmaking it an effective tool for interpreting and responding to the real-time shifts unique to this market.
In crypto, for example, we see pronounced effects from influential voices, whether it’s a tweet from Elon Musk about Dogecoin or announcements from regulators that send shockwaves across the market. Some traders use natural language processing (NLP) to assess the sentiment of social media posts and press articles and assess whether a statement is positive or negative. By doing this, algorithms can react faster than any human and take positions that align with expected market sentiment. But while these models can be incredibly powerful, they must be used with caution as their reliance on ‘the masses’ can sometimes amplify irrational market movements.
Furthermore, machine learning algorithms can be trained to identify market patterns, which can then support trading decisions. But machine learning is not a ‘set it and forget it’ solution. It requires constant refinement and adaptation, especially in a market as dynamic as crypto.
There is no doubt that algorithmic trading offers clear advantages over manual trading in terms of speed, scalability and consistency. Algorithms do not tire, are not guided by emotions and can execute transactions 24/7, qualities that are invaluable in the fast-paced world of crypto. Yet manual trading still plays an important place, especially in long-term strategies or scenarios that require human judgment and flexibility.
A common myth is that algos will always outperform manual trading, but that is not the case. Rather than replacing traditional approaches, algo trading works best as a complement to them, combining the efficiency of automation with the insight of human experience.
Institutional tools for all traders
One of the most exciting developments in the algo trading landscape is the increasing accessibility of tools like NLP and ML. Today, even relatively simple strategies, such as setting an automatic buy order when a specific 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 empowering a broader group of market participants to compete and implement their own strategies.
As the crypto market matures, algorithmic strategies must evolve with it. Trends like meme coins require flexibility from algo traders. New regulatory frameworks, such as MiCA in Europe, are also creating complexity as compliance and market adaptability become increasingly necessary. Innovations such as decentralized exchanges and new mechanisms are also likely to influence trading approaches in the future.
A more resilient market with Algo Trading
Ultimately, algo trading helps build a more resilient market, where information is incorporated into prices more efficiently and trading decisions are made more systematically. Retail access to these tools also promotes a diverse market.
Going forward, responsible algo trading can drive growth and resilience in digital asset markets, making crypto the future of finance.
