What is a FFT then? A FFT is an error that occurs when the user attempting to buy or sell shares accidentally hits additional keys to those they are targeting. The Hindu Business Line provides a nice lists of examples of these errors. The error normally results in trades being made for 10 or 100 times as much as intended. As you will find out, context is everything for this type of error. No big deal if you are working on your home computer and are able to correct the mistake but when dealing with amounts in the millions, this can have a huge impact upon the companies involved, and as listed above, an entire market.
The problems don’t end there. Occasionally a FFT can have even worse consequences for the company involved. In December 2005 the Times reports an instance of a FFT occuring at the Japanese company Mizuho Securities. Instead of selling 1 share at 610,000 Yen, the employee typing this in accidentally sold 610,000 shares for 1 Yen each. Not only did the error result in huge monetary discrepancies but the company actually sold far more shares than they had, in fact it represented “more than 40 times the total number issued by the company”. Yikes.
How easy is it to place checks and guards into trading software to ensure that trades aren’t made for 40 times the company’s worth? The task seems a trivial one so why has it not been implemented? It could be that in the dynamic and changing world of financial trading the task would involve a fair amount of computation. But these are just the type of calculations that most pieces of financial trading software are made to deal with. We could explain the lack of safe guards on poor User Centred Design. The companies commissioning the trading software will focus on the efficiency and speed at which their employees are able to trade at. In the fast moving world of stocks and shares speed is key to buying lowest and selling highest (fact generated by me based on films I have seen). There is no incentive for the software to be designed to do anything else any better.
Well it seems like feedback from these errors is reaching those in charge of designs. This article in the Sunday Morning Herald of Australia suggests that the FFT is being weaned out due to increased checking in the trading software – fantastic. Turns out it wasn’t an impossible problem. The article speculates that perhaps the recent dip in the Dow index was not down to a FFT but rather some error resulting from the program itself. At this point it isn’t human error, I say hooray and leave the analysis of the computer program to someone more interested in analysing the code of financial trading systems than myself.
One last thought on the FFT example from Mizuho Securities – is this a FFT at all? It seems like the issue here wasn’t pressing additional keys by accident but rather confusing the two numbers and entering them into the wrong locations in the interface. This could have been caused by a confusing interface or a lack of experience or simply mixing the numbers up in the employee’s head. It seems that the term “Fat Finger Trade”, in the media at least, is being appropriated for all types of error that occur in the financial market. How important is this generalisation? Well if we just want to read about traders doing stupid things, it’s a pretty useful search term. But, as a student researching types of number entry error, I really think this generalisation hides the more interesting information. If we break the generic FFT error down into more accurate descriptions of what’s going on, we can begin to look at causes (were they distracted? keyboard too small? numbers too hard to read? numbers too similar? confusing interface? no training?), and the myriad of possible cures.
So newspapers, you can have your buzz words but when you the reader see it, think about what’s really going on – it’s far more interesting.