What is Machine Learning and Why Should Advisors Care?

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What is Machine Learning and Why Should Advisors Care?


By: Brendan Ryan, CFA

From Siri and Alexa’s ever-increasing sophistication to the frightening accuracy of Facebook’s “people you may know” feature and Google Search’s predictive text, some of the world’s largest companies utilize machine learning and AI to translate massive amounts of data into insights about human behavior on a previously unimaginable scale.

Machine learning automates the discovery of predictive algorithms that can continuously improve as they get access to more data, and its potential impact on the investment management space is vast. But how precisely does it work and how could that translate to measurable results in portfolio performance?

As the technology evolves and becomes ever-more integrated with investment systems, advisors and investors alike will need to become familiar.
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Watch our resident machine learning expert, PM Brendan Ryan, provide a brief introduction below:

The topic is dense and we’re just scratching the surface, so stay tuned here on the blog, Twitter, and LinkedIn for future videos with additional insights.

If you’re looking for a strategy that can pursue alpha while maintaining built-in defensive capabilities, contact one of our regional consultants.

This article was contributed by Beaumont Capital Management, a participant in the ETF Strategist Channel.

For more insights like these, visit BCM’s blog at blog.investbcm.com.


Transcript:

Welcome to “Minutes in a Minute”. The theme investment committee today was the economy. We’re generally pretty positive on the long-term prospects for the economy. The way that we like to think about is that in 2019, prior to the pandemic, you had a pretty strong economy.

We were able to seemingly successfully put it on ice for about a year, year and a half, and during that time both the federal government and the Federal Reserve injected a lot of stimulus into the economy. So now as we’re reopening, we’re taking what we’re pretty strong consumers before the economy—they were able to even strengthen their balance sheets during the brief recession—and now we’re reopening with ample cash in the system, and that’s driving what is so far been a pretty robust recovery.

Unfortunately, there are more question marks in the short term. Whether it’s job growth or inflation, recently coming in a little bit lower than expected, or on the other side, retail sales coming in a little bit higher than expected, the picture in the short term is a little bit murkier.

Add to this that the expanded unemployment benefits have just ended, so we’ve got a large source of stimulus being drawn out of the economy. This leads to a very interesting picture going forward, but the stock markets haven’t really reacted to it at all. So the markets have been, in a sense, boring while we’ve got a very interesting economic story going on.

This is causing our models that focus a little bit more on the short-term outlook to decrease equity exposures a little bit. It seems like equities are priced to perfection at a time when we maybe have more questions than we’ve had over the past couple of months.

So where we are more short-term oriented and more dynamic, we’re coming to increase fixed income exposures, but our models that take a longer-term outlook are still generally overweight equities.


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