Algo-trading, short for algorithmic trading, is when computers handle buying and selling of assets—like stocks or crypto—based on a set of rules you program in ahead of time. No human impulse, no guesswork—just code doing the heavy lifting.

These algorithms scan market data in real time (think: price movements, trade volume, timing patterns) and make decisions way faster than a human ever could. They can run 24/7, never sleep, and never panic-sell at 2 a.m. because of a headline.

For example, you could set up a simple strategy like: “Buy Bitcoin if it drops 5% in an hour, then sell it once it rebounds by 3%.” Straightforward logic, but lightning-fast execution.

Traders and institutions lean into algo-trading for a bunch of reasons. It allows for high-speed, high-frequency trades across entire portfolios—something that just isn’t feasible manually. 

Algorithms can secure the best available prices instantly, which helps cut down on slippage (the annoying gap between the expected price and the one you actually get).

Another big perk? No emotions. Algorithms don’t get scared, greedy, or distracted. That means fewer mistakes and a better chance of sticking to your trading plan—assuming you’ve programmed it well in the first place.

Zooming out, algo-trading also boosts overall market liquidity by increasing the volume and frequency of orders. That can make prices more stable and predictable because, let’s face it, bots don’t flinch when the market sneezes.

Of course, it’s not totally plug-and-play. Setting up a solid algo-trading strategy takes some technical know-how—or at least a trustworthy platform that does the heavy lifting for you.Bonus tip: Some common algorithmic strategies include arbitrage (taking advantage of price differences), trend-following (buying into momentum), and market-making (offering constant buy/sell quotes to profit from the spread).