Trading, be it stocks or crypto, is mostly about making the right decisions at the right time to generate positive returns. Every successful trade decision involves determining what to buy or sell and establishing the opportune time to execute an idea.
There are two common methodologies applied to investment opportunity evaluation: fundamental and technical analysis.
Despite the rather straightforward breakdown of methodologies, the analysis methods themselves are anything but simple. Fundamental analysis requires in-depth finance and modelling knowledge and is therefore primarily employed by sell-side financial analysts and professional investors. On the other hand, technical analysis requires a strong understanding of mathematical formulas. Traders must track historical data, keep tabs on current price action, and devise formulas to forecast future price momentum.
In the early days of cryptocurrencies, it was relatively easy to keep track of prices. This was because there were only a handful of crypto assets and a limited number of exchanges. As a result, traders could readily keep tabs on price changes and implement in-depth technical analysis. While it wasn’t exactly convenient, it worked well at that time.
Yet, as more investors began entering the market, the need for precise price discovery and fair trading took centre stage. Unlike stocks and indices, the crypto market operates around the clock, every day of the year, with no market holidays. This, paired with the constantly growing number of crypto assets and exchanges, makes it difficult for traders to track prices, perform technical analysis, and execute orders at optimal prices and at the ideal time. However, as more investors began entering the market, the need for precise price discovery and fair trading took centre stage.
As a result, many traders are increasingly turning to algorithmic trading systems to make the most of their crypto investments. Algorithmic trading, also known as algo trading, is the process of automating the entire trading process using mathematical algorithms and predictive models from historical, social, and real-time data of assets to execute buy and sell orders according to predefined parameters.
Effectively, algorithmic trading software acts like a personal assistant that works round the clock, continuously identifying optimal trade opportunities based on initial input. Once the applicable algorithmic criteria are met, the software automatically buys or sells the asset without requiring a user to log in to the exchange and execute the trade. By design, algorithmic trading systems can execute orders, single and bulk, at a speed, consistency, and frequency that humans cannot match.
Usually, the underlying algorithms reflect complex formulas paired with high-level predictive and mathematical models. Building an automated trading system requires technical expertise (coding skills), access to enormous amounts of accurate data, and a deep understanding of financial and mathematical models. Hence, it is quite understandable that many traders opt for paid, ready-made solutions that can be seamlessly integrated into their trading accounts with just a couple of clicks.
That said, algorithmic trading, albeit its popularity, is limited to an extent. It relies on historical and real-time data to predict future price behaviour. With the growing number of exchanges worldwide, each on standalone blockchains, gathering accurate data from every available source is becoming increasingly difficult. On top of that, most algorithmic trading software works only with blockchains that share similar characteristics.
This is where emerging technologies like AI (Artificial Intelligence) come into play. While the traditional finance (TradFi) industry is still trying to figure out how to harness AI, AI-driven trading bots have already positioned themselves as the next big thing. Compared to existing trading algorithms, AI-driven trading bots, order routing protocols, and other novel innovations offer crypto traders an edge by supporting high-frequency trading that ensures bulk orders are processed in microseconds.
Unlike conventional trading algorithms, AI-powered trading algorithms don’t need to be programmed repeatedly. Instead, AI is designed to operate independently by analyzing massive volumes of data to build unique trading strategies.
Additionally, AI trading bots can backtest these strategies across several variables and scenarios to refine the options further. This allows AI-powered trading algorithms to deliver better results than algorithmic trading systems, especially when trading crypto assets across multiple exchanges.
Take, for instance, FLUID. It is an AI-based smart order routing protocol doubling as a cross-chain liquidity aggregator. Leveraging blockchain technology and AI, FLUID offers near-instant prices and cross-chain settlements, paired with extremely low costs, high throughput, and zero counterparty risk.
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