Automation has become more of an enticing proposal in the last decade than ever before – chiefly due to steep advances across the (tech) industry. From the likes of Uber creating safe(r) and more convenient trips to the Apple Watch connecting all your smart objects together, our lives have never been easier.
Unsurprisingly, the finance industry has also jumped on the tech-train, creating what was never thought possible, through the birth of algorithmic trading (also commonly referred to as Automated Trading or Black-box Trading). Simply put, the process involves complex mathematical formulas and computer programmes to formulate and execute trading strategies. To many, the unthinkable has become a reality.
The popularity behind such a trading means would be evident even to the novice investor. No emotions, fatigue or margin for human error present when making trades. On top of all that, computers work a 24-Hour day.
Professionals in the industry have honed and fine-tuned these systems to a T, reducing error-margins even further while they chase suitable formulas for maximum returns. At first cautious, investors have also warmed up to the idea that a computer could go where man would meet barriers and limitations. This leads one to question the expendability of human traders if automation has become king.
No system is perfect…
After some of the marketing smoke has cleared, it is evident that algorithmic trading does involve emotions – the emotions of the programmer. A human built the system and so it has been fine-tuned to follow a pre-set number of tick-boxes that don’t always follow the route of reality. Secondly, this form of trading still requires a human monitoring it in case of meltdowns or the like. Traders also have to be on hand to fine-tune the system as each one has a limited shelf life.
Speaking of limited shelf lives, quantitative traders have been known to create their algorithms equipped with ‘time-bombs’ so they self-implode (lose effectiveness) after a set number of years or months. Such is the paranoia surrounding the sub-set of an industry where patents hold limited power and physical jobs seem to be waning.
The full extent to which conventional trading methods will be hit is yet to be seen. What is acknowledged, feared and embraced by the industry is that it is more of a when than an if.
In what can be seen as a bit of irony, the whole algorithmic trading phenomenon has paved the way for new jobs – the programming and computer science industries are flourishing, crunching code and translating finance theories into the next big automated thing.