- Summary:
- AI trading systems are designed to limit risks in times of high volatility - a characteristic embraced by crypto traders.
Ask any veteran trader, and they will tell you that trading is all about tilting risk-reward in their favour and finding opportunities to time the market effectively.
But how do you make the right decision?
You can accomplish it by analyzing terabytes of statistical data, such as historical performance, real-time price movements, social analysis, and macroeconomic changes, among other things.
However, as a human with limited capabilities, it is impossible to keep a tab on everything, analyze even development in real-time, and make split-second decisions. These activities turn out to be even more complicated when investing across cryptocurrencies.
Why so?
First, thousands of different cryptocurrencies exist compared to traditional investment solutions (stocks, bonds, etc.). While traditional investment products are usually listed on a handful of regulated exchanges, cryptocurrencies are hosted across hundreds of competing centralized and decentralized asset exchanges. On top of that, unlike the traditional stock market, the cryptocurrency market has no market holidays, takes no days off, and moves around the clock.
Trading Algorithms Can Only Go So Far
Back when cryptocurrencies first emerged, and there were only a handful of exchanges, it was easy to keep track of every price movement for the limited number of digital assets. As a result, early investors had ample time to run in-depth technical analysis, exploit arbitrage opportunities, and execute orders that returned generous returns. However, as the crypto market continued to expand, it became increasingly difficult to track what was happening across the broader market.
Fortunately, many traders started leveraging algorithmic trading – a trading strategy already achieving peak success in the traditional finance (TradFi) universe. As the name suggests, algorithmic trading is the process of automated trade execution based on pre-defined criteria. The underlying algorithm does the heavy lifting, shuffles through massive amounts of data in the blink of an eye, and can automatically place multiple trade orders simultaneously.
That said, algorithmic trading, despite its success and popularity, has limitations. Since it primarily depends on historical data and the real-time price action of an asset to predict future price behaviour, there are chances that the predictions might not always be accurate. On top of that, most algorithms have a short lifespan, especially in highly volatile markets.
Ultimately, algorithmic trading issues many automated instructions that can’t understand (and decipher) market situations like humans. For humans, it is easy to spot irrational market movements and respond accordingly, like massive order flow or fundamental announcements. By contrast, algorithms are designed to understand only the most-perfect scenarios. Accordingly, algorithmic trading systems often become unusable and erroneous in high volatility conditions, requiring constant optimization and retuning.
Additionally, since most of the algorithms are constructed by humans, there are chances of errors unfolding in the coding process as well. Besides, most algorithms are developed by organizations that don’t generally use financial experts or data scientists to build them. This can result in non-optimized algorithms running wild across the broader market.
AI Unlocks A Dimension Of Automated Trading
Realizing the shortcomings of algorithmic trading, an increasing number of investors are opting for AI (artificial intelligence) trading. Compared to algorithmic trading systems, AI trading systems are designed to limit risks in times of high volatility – a characteristic embraced by crypto traders.
Artificial intelligence (AI)-powered trading systems ensure optimized risk management based on continuous analysis of massive amounts of trading data, market trends, and even social media or blogging sentiment. Besides, AI trading solutions are ever-evolving, dynamic, and fully automated. As a result, they can automatically adjust to changing market conditions and don’t just consider historical data or real-time price movements to predict profitable trade opportunities.
Unlike normal trading algorithms, there is no need to reprogram AI-based algorithms. Instead, they can automatically adjust and operate independently without any human input. Moreover, AI trading systems backtest the proposed strategies across multiple variables to further optimize trade orders, thereby ensuring lower risks and better returns.
Take, for instance, FLUID’s AI-based smart order routing protocol and cross-chain liquidity aggregator. The product was built by a team of financial experts with high-level expertise in some of the most prominent financial institutions like BNY Mellon, Goldman Sachs, Bank of America, Visa, Citibank, and founders of leading digital asset OTC trading companies, quantitative firms, and popular blockchain organizations.
FLUID’s AI-powered solution solves the lingering problems of the digital asset market, such as liquidity fragmentation, lack of best price discovery and execution, market manipulation, cross-chain interoperability, price disparity across exchanges, counterparty risks, and much more. By leveraging the features of blockchain and AI, FLUID seamlessly aggregates liquidity from centralized and decentralized venues while guaranteeing low transaction costs, extremely low latency, and zero counterparty risks.