How to play rising rates - InvestingChannel

How to play rising rates

Dear subscriber,

Everyone fears rising rates…EVERYONE!

Big money financial advisors look at U.S. Treasury ETFs more every day.

Which creates HUGE opportunities in the financial sector…

Ones the average investor can leverage to enhance their portfolios’ returns.

Let me explain.

The top ETF searches by financial advisors heavily favored tech and growth companies.

That’s not much of a surprise given their recent volatility.

But there’s something fascinating from our TrackstarIQ data you need to see.

Treasury Trends

Let’s take a look at the trend of institutional adviser user searches for the U.S. Treasury 20+ Year ETF – TLT.

See anything unusual?

For most of January, the number of institutional advisors searching for the TLT ETF was muted, with small spikes here and there.

Yet the TLT garnered immense interest in February. The number of unique users searching each day regularly topped days in January.

That means new institutional advisors began watching the ETF in February on a regular basis, almost by double the previous month.

So, yeah…they’re worried. Or should I say “they’re shifting their focus.”

What’s their target? Financial stocks.

Bank on it

You might assume that just because the SPDR Financial ETF (XLF) and the Regional Banks (does this have to be capitalized?) ETF (KRE) aren’t the top searches that they aren’t worth talking about.

What you may not realize is how important the trends of those searches are.

Take a look at the number of unique institutional advisor searches for the XLF and KRE over the last couple months.

Outside of a major spike in early January (can we add arrows here?) , the trend highlights the growing search in the financials over time.

Let me explain why that is.

Banks (and some stockbrokers) profit off what’s known as “net interest income.”. Essentially, they borrow at the short-term interest rates and lend at the long-term interest rates. The greater the difference between these two, the larger their profits.

Now, most of us know that interest rates on short-term Treasuries are much lower than long-term treasuries.

What you might not realize how rising interest rates move much faster on long-term bonds than on short-term.

Here’s a hypothetical example. A bank borrows at the current 2-year treasury rate of 0.14% and lends at the 10-year treasury rate of 1.58%. That creates a spread of 1.58% – 0.14% = 1.44%.

Now, let’s say both rates double. That creates a spread of (1.58% x 2) – (0.14% x 2 ) = 2.88%.

Some banks are more sensitive to these rate changes than others. And some banks do a much better job of managing their assets than others. So there isn’t a uniform net interest margin across all banks.

What is worth noting is that, in general, changes to the economy and interest rates disproportionally affect the stock prices of regional banks compared to larger money centers.

Best of the banks

We know two things happen when interest rates rise:

  1. Net interest income increases
  2. Mortgage lending decreases

Banks heavily involved in the mortgage and lending markets should expect to see a significant drop in activity. That means up and comers like Rocket Mortgage (RKT) and Wells Fargo (WFC) might struggle.

On the other hand, banks like JP Morgan (JPM) that focused on growing their wealth advisory business stand to outperform their peers.

Other companies like US Bancorp (USB) and Synovus Financial (SNV) derive a significant portion of their revenues from commercial lending, which has shown reasonable strength.

For any companies in the financial sector, it’s worth spending the extra time to do your homework. 

Ask questions like: 

  • Where does most of their revenue come from? 
  • Are they over-exposed to one economic sector or activity? 
  • What’s their growth plan over the next several years?
  • Have they done enough with Fintech to position themselves correctly?
  • Do their fundamentals such as price to book identify the company as a value?
  • How sustainable is there dividend?

Downloadable Data Sets

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