What Is Intermarket Analysis?

For most of the 20th century, a lot of investors looked at the markets in isolation. For example, it wasn’t uncommon for someone investing in U.S. stocks to only look at U.S. stocks, and another person investing in mutual funds to stick to mutual funds.

But that’s not the case anymore. Today, investors have to account for a global market that is connected in so many ways it’s impossible for a human to see and understand them all. Looking at individual investments in a vacuum may have worked in the past, but it won’t work now.

There are two main reasons why this won’t work. The first is simply that the markets have got larger—much larger. According to the World Bank, the number of publicly listed companies around the world has grown from 14,000 in 1975 to over 43,000 at the end of 2016.

On top of this, investors have had to deal with the rise of new global economies (just look at how quickly the Asian economies have grown compared to the rest of the world), and entirely new asset classes (the ETF industry has gone from $0-$3.4 trillion in 24 years).

The second reason is that increased computing power, specifically artificial intelligence and machine learning, has made it possible to understand and analyze these global relationships. This type of analysis is known as intermarket analysis, a form of technical analysis that focuses on the relationship between different markets.

“Traders who look at stocks and other markets in isolation are doing themselves a disservice”
said Lane Mendelsohn, vice president of VantagePoint Software, an artificial intelligence-based software specifically designed for intermarket analysis. “It’s very plausible to say that what happens in one market halfway around the world can very easily drive and influence another market that you wouldn’t normally think was correlated."

Sometimes these relationships can be very surface level and obvious. For example, the S&P futures that open at 6 5 p.m. ET will usually determine whether the U.S. stock market opens higher or lower the following morning.

But other times the relationships can be harder to see with the human eye. Louis Mendelsohn had that problem, which is why he created VantagePoint. The software uses machine learning to discover hidden market patterns not seen by the human eye, and then generates incredibly accurate price forecasts.

“He realized we’re talking about thousands of pieces of data that would need to be analyzed to create this global market analysis,” his son Lane said. “He was trying to figure out how to analyze thousands of pieces of data and figure out how they work together to drive a stock like Alibaba.”

Examples Of Intermarket Relationships

Let’s take a look at some of the relationships captured by VantagePoint on one specific stock. In this case, we’ll use Alibaba Group Holding Limited BABA.

According to the software, there are 31 different ETFs, futures, and stocks that have shown a correlation to Alibaba. This means that they either informed the movement of Alibaba shares, or the other way around. And remember, all that is for just one stock.

Looking at the table above, it’s not exactly a surprise to see instruments like the Powershares QQQ ETF QQQ and the E-Mini S&P 500 futures impacting Alibaba, considering it’s a large cap tech stock. Others however, are a little more surprising.

You wouldn’t normally think of Dollar Tree, Inc. DLTR and UBS Group AG UBS as stocks that are correlated to the second-largest e-commerce company in the world. But that’s what artificial intelligence gets you—a way to detect the previously undetectable relationships that make intermarket analysis easier.

Vantagepoint is a content parter of Benzinga. Click here to learn more or get a free demo.