The Mechanics of Algorithms in Online Trading Platforms
When most people think of stock trading, they think of a group of traders in a room trading loudly while holding a stack of papers above their heads. That's old-school stock trading. These days, much of the trading takes place in silence, and in many cases, electronically, based on algorithms running at lightning speed. If you have ever downloaded a trading app or have read anything pertaining to "algo trading," you've seen how this trend has quickly taken over so much of trading—regardless of whether you realize it.
At the most basic level, an algorithm in trading is simply a set of rules that tell a computer how to act. Instead of a human being watching a chart and determining when to buy or sell something, the algorithm will apply pre-programmed logic based on various drivers such as price, volume, or even breaking news. These aren't random actions; they are actions dictated by business rules developed from data, back-testing, and mathematics.
There are two key reasons: one is speed. Algorithms can process large amounts of market data and execute a trade in milliseconds, far faster than any human. But that's not the only aspect. Algorithms too don't factor emotion into the equation. Humans will panic, get greedy, or attempt to wait for the "right" moment. An algorithm will just execute based on the plan implemented, 100% of the time.
When you press “buy” on your favorite trading app, your order won't just instantly show up in the stock exchange. There's a lot of behind-the-scenes magic taking place where algorithms direct your trade to multiple exchanges and liquidity providers in order to find the best price for the trade. The trading platform might even utilize algorithms to route your order immediately to someone looking to sell at a fair price.
At an institutional level, institutions are using advanced algorithms for high-frequency trading (HFT). They can perform trades at lightning speeds for pennies on the dollar across huge volumes of trades and they do this faster than other players—sometimes by microseconds or milliseconds!
Recently artificial intelligence has added another dimension. Conventional algorithms follow explicit instructions, whereas AI-fueled algorithms can learn. They can learn from new data, identify patterns that were not previously programmed for, and alter recommendations without additional programming. This includes AI evaluating news articles, earnings reports, and social sentiment to evaluate how the price of a stock may react in the market.
Algorithm trading is not perfect, there are many challenges associated with it. Since so many trades may be automated, small glitches or unforeseeable mechanisms can rapidly rumble through the market. There have been stories of erroneous algorithms contributing to “flash crashes” - decreasing prices by gigantic margins in seconds only to revert back to previous levels shortly after.
But still, the algorithms aren't all equally functional. Large institutions have modern technology and mega-datasets, which no doubt gives them a far better advantage over everyday traders. That's why it's so crucial to learn about these systems before you go down the rabbit hole.
Even if you don't plan to be a day-trader, algorithms impact your market prices you see every time you tap on a finance app. The prices you're charged on stock trades, ETF prices, what you pay for crypto, it's all influenced by algorithms. Knowing they are out there, and knowing how they work even a little bit, can help you make better choices regardless if you are a long-term investor or taking the leap into active trading.
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