You’ve probably heard or read about the Dogs of the Dow theory before. If you’re already familiar with it, don’t worry, this article isn’t just a rehash of that.
The Dogs of the Dow theory is one of those theories that pops up every now and then, particularly when it comes to talk of how to beat the market.
And that’s what everyone wants to do isn’t it? If all we wanted to do was match the market, then life would be much more simple. All we would do is park our funds in an index tracking ETF and leave all the worrying to the stock pickers out there.
It would also save on countless hours of work — reading through reams of financial data and company reports. Let’s face it, probably not most people’s cup of tea.
The Dogs of the Dow theory revolves around a basic premise. While share prices might go up and down, it’s the dividends a company pays out over the years that will attract long term investors.
If you’re not familiar with how the theory is applied, the idea is that you buy ten stocks in the Dow Jones Industrial Average (DJIA) with the highest dividend yields on 1 January, putting equal amounts of capital into each. You then rebalance the portfolio at the start of the following year.
Stocks that are no longer in the top 10 dividend yield rating (or have been dropped from the index) are replaced with those that are. Those that follow the theory precisely also rebalance all ten stocks to ensure they all have equal weighting in the portfolio to start off the New Year.
Of course there are variations on the theme. One is picking stocks whose share price has performed the worst over the previous year. And there are variations on variations. Some allocate more weight to the worst performers as this will see the greatest returns if these companies come back into favour.
It’s worth noting that this theory applies specifically to the DJIA. That’s 30 of the biggest (or most significant) companies listed on the New York Stock Exchange and the Nasdaq — think Exxon Mobil, Johnson & Johnson, General Electric, and Apple.
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Another premise is that these companies will avoid lowering or cutting their dividends so as not to upset their shareholders. Given a stable dividend, a higher dividend yield implies a lower stock price. That is, a stock that is out of favour — something that should reverse when sentiment towards that company or sector changes.
And as the theory goes, these stocks that return to favour will increase in value more than those already in favour, leading to an outperformance of the index.
Proponents of the theory swear by it. Others point to all the years where it didn’t work. Like many of these things, the results are determined by where you start the data from. Either way, I’m sure the brokers of those that follow the theory look forward to their annual call in January.
Whatever your take, you can probably see how the theory can be applied to other markets.
One place where this theory has been applied is trading Australian bank shares. Here the idea is very similar, although I’m not sure if 1 January holds as much significance.
The idea is that you switch out (or reduce your holding) in the bank share with the lowest yield and put those funds into the bank share with the highest yield. Again, the idea is that the bank share with the highest dividend yield is the most out of favour. When sentiment changes, this bank stock should outperform the one with the lowest yield (or, whose share price is the most stretched).
You can no doubt see that there are several premises behind this theory too. The first being stability and growth of dividends. All of the major banks have enjoyed a great run over several decades, steadily increasing their dividends along the way.
Of course, it hasn’t all been smooth sailing — there have also been plenty of hiccups. But in broad strokes, all have been carried along by a quarter century of GDP growth and buoyed by a housing market that in the main has so far only gone one way.
The other premise here is that the yields are treated equally. But in fact, they’re not. There has always been a pecking order in the major banks. The strongest has historically traded on a lower yield, reflected in the premium given to its share price.
The trade therefore becomes reducing the weighting in the bank whose current yield is trading the most below its long term average (higher share price), and allocating those funds to the bank whose yield exceeds its long term average by the most (lower share price).
You can see how this theory might work when everything’s humming along. But 2016 might be the year that changes all that. The pecking order in the banks could be set to spread further.
Rather than rolling in and out of these bank stocks based on yields, 2016 will be the year that truly tests whether these yields are sustainable. With the Clydesdale demerger, some analysts are already lowering NAB’s [ASX:NAB] dividend forecast by at least 10 cents this year.
There’s also the increasing capital requirements lurking in the background. Whichever way you slice it, banks will need to hold more capital at the same time their profits will come under pressure.
Following the Dogs of the Banks theory and flicking out of the lowest yield bank and into the highest yielding bank might not work this time round. Also, allocating funds to the highest yielding bank could come unstuck if they’re forced to reduce their dividend, or start to run out of franking credits — something ANZ [ASX:ANZ] shareholders might need to face.
On current estimates, Commonwealth Bank [ASX:CBA] is the only one that looks like it has the power to increase its dividend this year. Although it, along with the other banks, is going to be put under pressure.
2016 will be a tough year on the market, banks included. It will also be a time when the market finds out what a business is really worth. Rotating in and out of bank stocks based on yields might now prove to be a trade past its use-by date.
Over at Total Income, I spend most of my time hunting up the best dividend plays for 2016. You can find out more about that here.
Ed Note: This is an excerpt of an article originally published in Markets and Money.
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