Choose Your Own Trading Adventure

Last September, Amazon opened up the first of its physical stores, containing products that appealed most highly to customers near that location. In December, Netflix released Bandersnatch, an interactive film in which the viewer is able to choose their own path for the story. Personalization has become the norm, and it will soon become the expected experience in the trading world.

The most critical requirement for personalization is data – not just its collection but the way we format, categorize, and interpret it. Just as every consumer develops a pattern for the products they purchase and every viewer has a preference for the films they enjoy watching, every trader has a personal style in the way they trade complex orders, seek liquidity, and react to market conditions. The trading systems of the future will aim to capture that style and leverage it to target alerts for trading strategy optimization. Imagine, as a trader, if you had a system that monitored for every market condition you cared about, tailored that condition to each of your particular orders, and then applied its knowledge of your trading patterns when alerting you with possible actions to take.

Just as each of our Amazon and Netflix homepages show different content, every trader’s experience will be different from that of the trader sitting at the next desk. And taking consumer-driven product design a step further, just as Amazon and Netflix allow users to rate their experiences with their products as a subjective metric that compliments the objectivity of active usage, traders will be able to rate their experience with their trading systems, which will in turn be fed back into their design.

Applying the trends seen in other industries to financial services, the implication is that the most intelligent trading systems will be the ones that access the most powerful data and have a good design for delivering that data to its users. The last thing a trader needs is an overload of inconsumable alerts or yet another grid. The most effective trading platforms will determine the right balance for alerting users at a consumable pace so that traders have time to take action, employ a design that is visually captivating but not distracting, and be intelligent enough to know when the user is likely to care more than usual about a particular data point.

The human and the machine effectively become a check-and-balance for each other. The machine weighs in with its perspective on an optimal trading strategy based on years’ worth of data points that brought it to its conclusion, and the human uses judgment to recognize when key considerations are missing and feeds this back to the machine.

Another interesting outcome of trading pattern identification may be the formation of new trading communities. If a trading system is able to capture parallels in sought content and traders’ responses to that content, it will be able to categorize trading styles in a more precise way than ever before. A trader may have a similar style to someone on another trading desk in a different part of the world, and it will be the trading system that identifies and connects these two people.

If trading products follow consumer products, we should expect that the future of trading will involve scrolling down streams of personalized trading notifications on your mobile device, pinch-to-zooming on price and volume charts, seeing how many traders liked each notification, how many had your trading style, and changing your trading strategy with just a few taps.

Natasha Shamis, Global Head of Product, Liquidnet

Ellen Gordon