“In good information visualization, there are no rules, no guidelines, no templates, no standard technologies, no stylebooks… You must simply do whatever it takes.” – Edward Tufte

Whether you are a consumer or purveyor of data for the application of financial markets risk transfer, there’s something in here for you.

Let’s start with a quick trip in the Wayback Machine:

In a report that I authored for TABB Group that was published in June 2011, “Quantitative Research: The World After High-Speed Saturation,” one critical concept presented there that has proven itself to stand the test of time, and I expect to continue to do so for the foreseeable future, is this:

“As strategies and quant directives change, the need for effective communication with stakeholders will march in parallel. Though quants are not usually known for their silver tongues, we strongly encourage them to meditate on one word: pictures.

Rather than turning your backs on spreadsheets, embrace them as the best solutions for reporting, visualization, collaboration and concept development. At the higher end, enhanced information design techniques are the best panacea for navigating the scale and complexity of oncoming data challenges.” 

Now, occasionally, I have expanded on this “a picture is worth a thousand words” theme to hammer the point that information design is critical to bridge the gap between us humans and our ever-advancing data flows. In a world like ours, in which data is everywhere but usable data is not, we must pay much closer attention to how we interact with the data gusher we all now find ourselves on the receiving end of.

In other words, design can mean the difference between capturing opportunity or suffering the consequences of missing it. The challenge is no longer in relation to computational power, but in the ability to climb steep learning curves quickly and to dramatically increase the density of information flow via limited computer screen real estate.

In any case, today, I’m here to amp the message a step further: The “interface” – the picture, the dashboard, the portfolio of visual metaphors, or whatever terminology resonates most profoundly with you – IS the thing that not only augments cognition between you and the data, BUT ALSO augments the transfer of cognition between you and your colleagues who have responsibilities at different points in the workflow than you do. Moreover, given the increase in the quantity and diversity of data flows, new human-computer interface (HCI) designs will be required to allow end users to absorb the dramatically new levels of data necessary to be competitive in the current environment.

If you question this logic, I invite you to meditate on one more word: Bloomberg.

When the demand for quantitative researchers and data scientists shifts to a fervent demand for video game designers, you will know that this theme has taken root. Though they will always have a place in the toolbox, we must graduate beyond 2D grid-based layouts and limited factor display to multi-dimensional and interactive layouts with N-factor display. (Full disclosure: Having earned a patent on a high-density N-factor display, I am talking my own book…)

Meanwhile, as the quantitative revolution continues to become more pervasive – and the balance of personnel shifts more towards those with analytical, left-brain tendencies as workflows become more automated – the supply of personnel wielding visual creativity skills is decreasing in our industry. The mass consolidation of trading platforms and other fintech solution providers doesn’t help.

So, here’s some friendly advice for those who are attempting to sell (alternative) data into the trading and asset management world: Put a skin on it. The data will sell better if it is driving a picture. It’s just an example; a use case. It need not be the end-all or be-all.

Now, as for those of you tasked with investing in new datasets to drive trading and investment activities, here’s some friendly advice for you, too: Don’t leave it all to the quants. By default, quants don’t care about dashboards or visual metaphors or visual creativity. They only care about consuming data with pattern recognition tools. Instead, invest in some right-brain talent, either on a full- or part-time basis, and have them work to get your data to sing some different tunes.

The success of your hedge fund or prop trading performance is not only dependent on being creative with the assembly of data, but the variance and flexibility of perspective on that data, too.

Alphacution is here to help.

Watch this space…