Andreas Polycarpou: “High-Frequency Trading And Algo Traders’ Experiences”

Algo trading has made the financial market seamless for traders. With the automated process based on computers and clever mathematics, traders can buy and sell in the blink of an eye. Andreas Polycarpou explains high-frequency trading and shared practical experience that error traders might experience when using high-frequency trading.

How does high-frequency trading affect traders?

_Andreas Polycarpou

Andreas Polycarpou says, “The advent of technology has made trading more exciting and seamless to perform by traders. However, it is important to note that there are still many risks involved when using high-frequency trading. Most high-frequency trading algorithms respond swiftly to the dynamism of the electronic trading floor. These high-frequency systems move too fast for humans who keep track of what the computers process. Hence, high-frequency trading makes it possible to lose almost half a billion dollars in about an hour plus.”

“To provide a practical idea of the rate at which high-frequency trading works, the high-end trading computers would have completely performed about 165,000 different trade sessions before Usain Bolt, the renowned athlete, reacts to the starting pistol. This appears crazy and unfathomable; however, it’s a good one for traders who want to do much in limited time so far they are ready to bear the brunt of the risks attached” – continues Andreas Polycarpou.

High-frequency trading and traders’ experience

Andreas Polycarpou narrates, “The experiences humans have had with high-frequency trading are unique and relatable since no one can have too much of anything good. Humans keep watching high-frequency trading, but with no ability to track the workings of the computers. For instance, at Knight Capital, a computer glitch cost a loss of about $10 million [£6.4m] a minute. The loss started immediately when the system was switched on. The traders at Knight Capital were buying high and selling low over an extended range of times per second and losing 10 to 15 dollars each time. The loss eventually cumulated to a whopping sum of $440 million [£281m] after 45 minutes. ”

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