How Behavioral Analytics is Shaking Up the Retail Trading World

When the European Securities and Markets Authority introduced its product intervention measures in August of last year, it in part justified the move by citing client losses. Retail traders, the regulator said, were losing too much money.

Although you wouldn’t know it from the language ESMA used, that’s always been the case. Even back in the 80s, when the internet was in its infancy, and Mark Zuckerberg but a twinkle in his father’s eye, around 80 percent of retail traders lost money.

But regardless of what you think of ESMA’s rules, they are here to stay. Given that’s the case, and as brokers must now clearly state what percentage of their traders lose money, it makes sense for them to boost the number of winners they have using their platform.

One way to do that is to introduce tools, grounded in behavioral economics, to try and get traders to improve their skills. Previously

confined to academia, various products drawing on behavioral psychology have been brought to market over the past 15 years.

Many of these have targeted the institutional world, but a number of products have now been brought to the retail market.

“We help traders by applying psychological research to their own data,” Ann Hunt, the chief executive officer of Chasing Returns, told Finance Magnates.

“Using models informed by recent behavioral research and research in machine learning, we can present traders with simple metrics that help them understand their trading habits and ways they can improve their trading performance.”

Making it work

Advances in technology have certainly helped firms like Chasing Returns, which was launched in 2014, take their products to market. But, though they can use this technology to provide traders with some behavioral insights, there is some controversy as to its efficacy in improving profitability.

Capital.com, a broker which launched in 2017, has used its machine learning offering as an underpinning to almost all of its marketing efforts. That technology is, according to the firm, being used to monitor traders’ behavior.

And yet a quick look at the broker’s website shows that it isn’t faring much better than its competitors. In the most recent three month period which the firm surveyed, 76.2 percent of its clients lost money.

To give Capital.com their due, this figure is rather misleading. Speaking to Finance Magnates in January, the broker’s CEO, Ivan Gowan, noted that traders were actually profitable around 62 percent of the time - they just lost more than they had earned in the remaining 38 percent of trading.

It’s also worth noting that the firm has seen a steady decline in its number of losing clients since January when it introduced eQ, a system which, using artificial intelligence, can analyze traders’ behavior and give them pointers on where to improve.

“We recalculated our win/loss ratio for the last 12 months, which takes into account the first three months of the launch of eQ,” Gowan said this Wednesday. “The percentage decreased from 81% to 76.2%, which is further evidence that clients who read and act on the eQ messages tend to improve their overall performance.”

Building the right tools

In his January interview with Finance Magnates, the Capital.com CEO also hinted at another problem brokers face when bringing technology to the market - they can’t make them use it. For instance, even if you tell a client that they should use stop-loss orders, that doesn’t mean they are going to do it.

“In order to build a tool that actually has an effect you should have a decent understanding of psychology, human behavior and trading,” said Oded Shefer, the CEO of behavioral analysis firm CPattern.

“Then when you have a concept you start small, collect data and continue developing and refining it based on that data. You also need to make sure traders like the tool and adopt it. So there is a delicate balance between having an effect and making users adopt the tool. It is a real challenge!”

If brokers do manage to create a decent product, it does seem that behavioral Analytics can help their traders do better. Capital.com, for instance, found that just using stop-loss orders would make trading more profitable for around 70 percent of their clients.

“We have been researching ‘the functional dynamics of thought and the decision-making process while trading the financial markets’ for ten years now,” said Ken Medanic, the founder of NeuroTrader, a company that, using biodata and psychological research, is creating wearable devices to improve traders’ profitability.

“We have empirically-based evidence which clearly shows the positive impact analytics tools can have on the performance of traders.”

More analytics, higher volumes

Of course, it’s possible that many brokers are not concerned with their clients’ profitability. With most companies reporting similar win/loss ratios, having the bulk of your clients lose cash may not look great, but they aren’t going to find anything much better elsewhere.

But that doesn’t mean behavioral tools can just be cast aside and dismissed as a waste of time. As they have clamped down on leverage, ESMA’s rules mean that brokers are looking for ways to get their clients to trade more and boost volumes. Behavioral psychology-based solutions can help them do that.

“We have seen that better revenues can be achieved by improving the caliber of your traders,” said Hunt. “Brokers using our solutions have seen a significant increase in trading volumes and engagement among their traders.”

There are two main reasons as to why tools, like those offered by Hunt’s firm, boost volumes.

For one thing, they imply that a broker is investing in their clients beyond the standard, and often lackadaisical, educational efforts put out by firms. Regardless as to whether or not a trader actually improves, that’s something they are likely to appreciate.

Arguably more important is the fact that traders have a better understanding of themselves and brokers have a more complete picture of the psychological makeup of their client base.

If, for example, you know a client will trade more volume and more successfully based on certain indicators, you can push news of those indicators to them. Similarly, if a client thinks there is a solution to their trading problems - using stop-loss orders for instance - then they will trade more to see if it actually works.

Riding the wave of change

Having said that profitability isn’t relevant to some brokers, it’s also the case that there is a growing demand for different services which mean companies may struggle if they plan on just b-booking their clients into the dust.

For one thing, clients are asking for direct market access and straight-through processing in the foreign Exchange markets. Perhaps more significantly, they are also asking for commission-free stocks trading.

Adopting either of these two products will have to lead to a change in business model for firms. I’ll leave it to the brokers to figure out what that business model should be but, whatever they do, it’s almost certain that more trading volumes will lead to more money for them.

Here the same aforementioned factors regarding behavioral analytics tools and client engagement come into play. The only difference here is that the b-book model would, one hopes, become redundant. Thus, if we assume a profitable trader is more likely to continue using the platform that has brought them success, better traders would genuinely be good for firms.

“Creating more profitable traders is definitely the right way to go and this would mean that the business model of most brokers has to change,” said Medanic. “I hope that ESMA regulations and technological change can be an impetus for that.”

Whether or not that happens remains to be seen, though undeniably the retail trading world is transforming.

Behavioral analytics tools look set to be a part of this change and, whether brokers hold on to their b-book model or look to change the way do business, those tools can help them make money.

For all the traders out there, prepare for some data-driven mind reading.