There’s a trading pattern called the “January Barometer,” which suggests that the performance of the markets in the first month of the year might predict their direction for the rest of the year.

But does it really work? To find out, we tested this theory using over 100 years of historical data from the Dow Jones, to see if it’s truly a winning strategy or just another baseless myth.

In this video, you’ll discover:
•A deep dive into the "January Barometer" and whether it’s actually effective
•The results of testing it on the Dow Jones
•What to do if this pattern doesn’t hold up in future years

Watch the video now to uncover all the details and decide if following this pattern is worth your time!

Transcription

January Barometer—what is it all about?

There’s a phenomenon known as the January Barometer in the stock market.

According to this theory, the performance of January can provide insights into the remaining eleven months of the year.

Specifically, a positive performance in January might indicate a favorable year ahead, while a negative performance could signal greater challenges in the months to follow.

In this video, we’ll analyze, through a backtest, whether this recurring pattern, when properly exploited, can actually generate profits, or if it’s just another theory with no practical value when applied to the markets.

Analyzing Dow Jones market data

To do this, we’ll analyze data from the Dow Jones.

Alright, here we are looking at the Dow Jones chart on a monthly timeframe.

In other words, each bar you see represents one month.

Now let’s go ahead and take a look at the strategy’s code, and as you can see, the January Barometer only requires two lines of code.

Specifically, let’s check out the entry rules. We see that there are just two conditions here.

The first rule is that we must be in the month of January, as the trade will be executed in February.

So, if we are in January and the closing price of the bar is higher than its opening price, then we buy at the next bar at market.

Just a reminder: since we’re working with a monthly timeframe, saying that the closing price is higher than the opening price, I simply mean that January must be a positive month, because it’s close is higher than its open.

As for exiting the position, the rules in this script are even simpler.

If we’re in the month of December, we close the position on that bar’s close.

In other words, we want to exit the position on the last trading day of December.

Alright, so now let’s go on and apply the strategy to the chart. As you can see, I had already added it earlier.

However, we need to make a small adjustment.

Since we’re dealing with stock indices or equity markets, we won’t purchase a specific number of contracts as we would do with futures. Instead, we’ll invest a fixed capital amount per trade.

In this specific case, I’ve set the strategy so that we use a capital of one million dollars per trade.

This is simply because, over the last period, we’ve seen the Dow Jones trading around the level of 40,000 points. Therefore, in order to ensure greater trade efficiency, we’ll invest one million dollars per trade.

It’s purely a matter of optimizing the number of contracts we can use when opening our positions.

This obviously means that when talking about metrics like average trade or net profit, we’ll analyze them in percentage terms.

Alright, so let’s go and have a look at our strategy on the chart. As you can see, we already have two trades that follow the conditions we discussed earlier.

For instance, here we can see a January bar. The bar close, here on the right, is higher than the open, meaning that this January was a positive month. In this case, the strategy opens a long position on the first trading day in February.

As you can see, after staying in the market for 11 bars, that is, 11 months, we from 1close the position in December, specifically at the close of this bar.

But let’s go and have a look at the strategy performance.

Here, as you can see, we have an upward-sloping equity line.

This strategy performed pretty well over the entire period used for testing it, which includes market data starting from 1950 up to the present.

What happens when January delivers positive results?

However, we notice that it performed particularly well in certain decades, more specifically from 1950 to around 1970, and from 1980 to the 2000s.

Then we also see two flat periods where no significant profits were made.

Specifically, this one here and this other one here, which corresponds to the last two decades.

Taking a closer look at the Average Trade for this strategy

Alright, with that said, let’s analyze the average trade of this strategy in this specific case. In other words, let’s figure out how much it yields on average per year.

As you can see here, we’re looking at an average trade of almost $100,000.

Considering the initial capital allocated per trade of $1 million, this equates to about 10% per trade, which means 10% annually.

It’s also worth noting that, since 1950, 43 trades have been executed, with a profitability rate of 83%.

However, this analysis alone isn’t enough to claim that the January Barometer really works.

What about a negative January?

To prove it, we need to check what would happen if we used the opposite condition—that is, what would happen in the case of a negative January.

This takes just a moment to adjust. We only need to change one small thing in the code.

Instead of requiring a close higher than the open, we need to set it so that the close is lower than the open.

In other words, let me reiterate: we need a negative January, with a negative performance.

Let’s compile the code and take a look at the strategy.

Here, in this case, obviously, we’re looking at different trades.

Here, in this case, for example, a long position is opened in February after a January that ended with a negative performance.

In fact, it was opened here, and then the bar closed here.

Alright, at this point, let’s evaluate the performance.

I’d say, at a glance, that we’re looking at an equity line that’s much less consistent than the one we saw earlier.

Essentially, starting from 1950 until 2000, we can say that it neither gained nor lost.

However, if we analyze the last two decades—starting from the early 2000s to 2005 onward—we notice that there were, all things considered, some noteworthy trades. This is quite the opposite of what we observed with the previous condition.

When we had set January to be a positive month, we saw that, in reality, the strategy hadn’t performed that well in the last 20–25 years.

Revisiting the Average Trade: does it hold up in a down market?

That said, let’s also go and have a look at the average trade of the strategy, its annual return.

Here, we’re looking at an average trade of only $37,000, once again considering the $1 million investment.

Well, considering that earlier we saw nearly 10% annually, here we’re looking at less than 4% annually.

So, the performance is significantly worse.

The same goes for the win rate. In this case, the win rate is around 50–56%.

What conclusions can we draw about the January Barometer?

In conclusion, what can we say about the January Barometer?

We’ve demonstrated that this phenomenon exists and can offer interesting investment opportunities.

However, by analyzing the two equity lines, we noticed that this pattern was significantly more efficient between 1950 and 2000.

Are we witnessing the decline of this once-reliable edge?

The question to ask, then, is: Are we witnessing a loss of this edge, or are the performances of the last two decades not necessarily indicative of a permanent change?

The only way to find out is to continue monitoring this trading approach while also diversifying your portfolio to reduce dependency on the outcomes of a single strategy.

If you want to dive deeper into how to achieve these goals, I recommend clicking the first link in the description.

And I’ll see you in the next video!

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