Bank Of America Is Leading The New Quant Research Arms Race

As the financial research industry drifts further away from being 100% human powered to relying upon split second decision-making based on data collected by a human/machine hybrids, Bank of America is seeking to lap the competition. The bank's head of global research, Candace Browning, has put together a squad of six people, including four PhDs that are going to team up with about 600 Wall Street analysts. According to Bloomberg, the goal of this group is to streamline quantitative analysis: spotting patterns in data sets before anybody else.

Of course, in order to find these patterns, analysts have to sift through enormous quantities of data, pulled from what are usually non-traditional sources - and haven't been spotted by others - in order to help forecast things like airline revenue, luxury spending and even the timing of the business cycle. Bank of America clients seem to like this type of analysis: these quant-enhanced reports get about three times more clicks than other publications that the bank delivers to its clients.

Browning explained BofA's quantamental approach to Bloomberg as follows: "It’s telling clients something they don’t already know. The future of Wall Street, the future of investing, is going to be aggregating and analyzing data in ways that give you a cutting edge on new information. Once you’ve done that, you still need the human factor."

The rise of quantitative analysis shouldn’t be much of a surprise given the fact that trading is moving more towards algorithms and high frequency electronic training. With quicker trading times comes the need for analyzing larger sets of data faster, which could be a laborious task. In fact, one can argue that robots are now writing research meant to be read by other robots - it's probably only a matter of time before it is written in binary.

All this takes place as banks are trying to keep up with the breakneck pace of evlution in the industry. In fact, other banks already have a head start: UBS Group’s "Evidence Lab" looks over billions of data points in order to analyze stocks while State Street distributes data on inflation that is based off of more than 5 million item prices sold around the world. Maybe the Fed could use some of these approaches to actually calculate what the real CPI is...

Meanwhile, Bank of America has found new techniques to survey hundreds of thousands of people about items like iPhones and driverless cars. The data scientists there have done a deep dive into credit card data to help measure home-improvement spending and have also crunched more than 100 economic variables beginning in 1959 to reach the conclusion that a United States recession isn't imminent. Some of the data is passed along to the bank's clients but much raw data collected in-house by Bank of America isn’t for sale.

Daire Browne, Bank of America’s head of global research client services told Bloomberg: “It’s an arms race. There isn’t this big divide anymore of the old-school, fundamental type versus the big, heavy quants.”

Robo portfolio manager shown her reading quant research

Of course, with robo research now growing by leaps and bounds, it is only a matter of time before robo portfolio managers take over Wall Street. Earlier this week we discussed how AllianceBernstein was using robots to come up with ideas for fixed income/bond trades. 

AllianceBernstein's new virtual assistant can suggest to fixed income portfolio managers what the best bonds to purchase are, using parameters such as pricing, liquidity and risk. The machine has numerous advantages to humans: "she" can scan millions of data points and identify potential trades in seconds. Plus she never needs to take a cigarette or a bathroom break.

The new virtual assistant, dubbed "Abbie 2.0", specializes in identifying bonds that human portfolio managers have missed. She can also help spot human errors and communicate with similar bots like herself at other firms to arrange trades. Most important, her greatest expertise is making humans - very expensive humans - redundant.