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How Big Data Analytics Help FAs Beat Volatility and Other Key Challenges

By Garrett Keyes December 3, 2018

Advisors are in store for challenging markets in 2019, says Candice Tse, head of U.S. market strategy for strategic advisory solutions at Goldman Sachs Asset Management.

But through big data analytics FAs can maximize portfolio returns and navigate the coming storm, she says.

"Moving ahead we think equity markets will return more muted returns than we have seen in the last few years. Not the 22% we saw last year, not the 12% we saw in 2016, but more so to the tune of near single-digits moving forward," says Tse.

Tse is not the only expert to point to big data as a powerful tool.

Michael Silver, CEO of $610 million AUM Baron Silver Stevens Financial Advisors, and Gauthier Vincent, lead wealth management consulting partner of consulting firm Deloitte, both suggest that by using big data, advisors can better adjust to changing market conditions and aid portfolio management.

Vincent says many investment platforms advisors already use (or those currently in development) can utilize big data to help the investment process in a number of ways. Big data analysis methods can include: harnessing real-time information on global events that move markets, automatically adjusting portfolios for volatility, and accounting for behavioral trends in stock buying.

“Let’s say I am doing investment research and I have a question about the impact of an earthquake in Indonesia on gas stocks,” Vincent says. From news articles to weather reports, there’s ample data available in real time on natural disasters and geopolitical events that can be inputted into databases. Vincent says with big data analytics, firms can interpret such information faster to help drive advisor best actions.

As well as reacting to the portfolio effects of natural disasters, FAs can also use big data analytics to adjust asset allocation when volatility shakes markets.

With big data analytics, FAs can determine which clients are most affected by volatility and know when to adjust portfolios, Vincent says.

And even the asset allocation adjustments advisors make can rely on big data. Investing used to be all about choosing the best stock in which to invest, but more and more it’s about changing the shape of the portfolio in real time, Vincent says. Some robo advisors are already doing that.

If the market moves, some robo advisors will send clients a tweet saying they should rebalance the portfolio for “XYZ reasons,” Vincent says. Real-time portfolio analysis capabilities will continue to improve with time, as algorithms become smarter and data cleaning, aggregating and organizing improves, he says.

Gauthier Vincent

Aside from real-time portfolio analysis, Silver suggests FAs can incorporate behavioral finance concepts and use big data to reap added portfolio rewards. For instance, investing often follows a herd mentality, and looking at overbought and oversold areas presents opportunity to create returns based on how other people invest, he says. For instance, Silver’s firm analyzes big data on fund flows and he says advisors generally want to do the opposite of the mass investing public. In tough markets, such a strategy can become particularly important, Silver says.

Using big data analysis, FAs can come up with themes to track – such as where they think markets are headed and how the global economic story may impact markets – and compare historical data to produce a better picture of what may happen in the future, Silver says. For example, “If the herd is going with indexing, will active managers have an edge?” Silver asks.

Speaking with FA-IQ, Candice Tse outlines how she believes big data can be used to drive alpha and traverse difficult markets.