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With the foundation of the survey in place, we were reasonably confident of collecting good quality data again. One of the notable features of the survey was that almost everybody who started the survey made it all the way to the end and answered all, or nearly all, of just under forty questions. That told us that the survey could have been longer. So, for we added a significant number of additional questions and included a section dedicated to regulation and market structure taking the final total to eighty six questions.
In addition to the opportunity of collecting much more detailed data, we were also conscious of the fact that in a disproportionate number of firms that participated in the survey were very focused on high frequency strategies. This is perhaps understandable given the number of Automated Trader readers that are algorithmically driven in their approach to markets, but the promotion of the survey to the people that had participated in an HFT webinar that we ran just before launching the survey and the relatively narrow focus of the questions served to compound this natural bias.
For , we also took the decision to run the survey for longer, with the extra time allowing us to promote the bigger set of questions to different sectors of the trading community.
What became apparent almost immediately was that not only was the participation level far greater than we had expected or hoped for, but again most people were completing the entire survey. As a result of the broader appeal and extra promotion, by the end of the first week we had had over one hundred completed results, and by the end of the second week the total of just over two hundred responses had surpassed the participation.
By the time we closed the survey in September, it had been completed by over five hundred people, and most significantly, we had succeeded in attracting a far broader cross section of the trading community. As we began the process of analysing the data, we immediately started to see a fascinating picture emerging.
All of the key trends towards automation and the adoption of algorithmic trading that we had identified in were still present, but the trends had clearly amplified quite significantly. Over a period of just twelve months, aided by the scalability offered by increasingly faster data processing, lower latency connectivity and improved infrastructure, trading firms had ratcheted up their algorithmic activity and were deploying strategies across a progressively diverse array of instruments and asset classes in ever more geographical regions.
Many firms that were previously using algorithms only to manage execution are now also reporting the use of a myriad of other models using highly diverse data and metadata right the way through the entire trade life-cycle.
Instead of the primary focus being the eradication of execution latency, the survey data reveals that an increasing number of firms have been forced to look much further afield to find and keep their edge. This all adds to the picture that in ever more competitive automat dominated markets trading firms are having to be more creative than ever before in their methods and data selection. Whilst many of these trends were apparent in the data, what is most significant is the scale and speed at which these trends are developing.
Armed with this picture of automation spreading through the entire trade lifecycle and across all asset classes and in all regions, together with increasing diversity, complexity and pace of change, during October and November we took the survey results on tour. Over the course of those events, what we discovered from the many conversations we had with proprietary traders, brokers, fund managers, technologists, academics and regulators was widespread agreement with the key points to emerge from the survey data, with many telling us that the results were very much in line with their own experience.
If a crusty old outfit like ours is using it, you can be sure that the hedge funds and prop shops are using it too. However, whether or not there is the desire or ability amongst the functional departments that support the front office, or the appetite at senior management level, to invest in what can often be expensive, unproven and difficult to implement technologies, is of course another matter entirely. Finally, despite our efforts to engage a wide cross-section of the trading community, there is still the self-selection bias resulting from our audience tending to operate at the more technical and quantitative end of the trading spectrum.
This should be kept in mind when interpreting the data. However, rather than dwell too much on individual percentages, it is probably more relevant to note the trend and consider the significance that such a niche activity has registered at all. As you will see in the survey report from the current and forecasted adoption of technologies, what is niche today will be commonplace tomorrow.
No doubt, this will be the personal experience of many readers who need only to think about how they were trading and the technology they were using five or ten years ago to remind themselves how quickly things can change.
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