Expect and Fear the Trading Bot

Be very careful ... 

I, Trading Bot

Algorithms are being unleashed on the crypto markets.

By Nathan Thompson  in CoinDesk

Opinion

 Movies about stock traders and investors often depict Wall Street mercenaries with great hair or uber-nerds wedded to their computers, but the age of the human trader is already a thing of the past. Welcome to the age of the “bot.”

Trading bots use algorithms that execute trades when certain market conditions are met. Since the early 2000s there has been strong growth in these bots especially as market data has become more sophisticated. Now the algorithms are being unleashed on the crypto markets.

Nathan Thompson is the lead tech writer at Bybit. This article is part of CoinDesk’s Crypto 2023 series.

Algorithmic trading is used across most capital markets. According to a 2020 report from the U.S. Securities and Exchange Commission, 78% of market trades were performed by “trading centers [that] depend on automated systems and algorithms.” Other commentators peg the volume of stock trades coming from bots at 60% to 70%.

Institutional traders rent or create their own bots that activate when the market hits certain conditions. These algorithms constantly search markets for the right trade setups, such as finding oversold stocks or trading a breakout. When they find the right conditions bots run scripts that determine the position size, execute the trade, employ stop-losses and exit automatically.

The bots are not perfect because they are created using past data, but the latest artificial intelligence (AI) and machine learning technology are already being employed – making them faster and more efficient than ever. Further, bots take the emotion out of trading (helping to stymie some of the emotional burden of investing in volatile markets).

See also: Become a Better Crypto Trader by Avoiding These Cognitive Biases | Opinion

“Reason is a slave to the passions” as philosopher David Hume said, and humans are by definition constantly at risk of making bad decisions based on emotions. For example, the infamous “revenge trade” happens when a trader fires ill-advised bids into the market in a desperate attempt to recoup a large loss, usually compounding their defeat.

More insidious is the fact that people don’t like being wrong. This makes them stay in a trade too long out of an irrational attachment to the company or digital asset when exiting is the best strategy.  ... '