Quotes about Life Tell me not, in mournful numbers,
Life is but an empty dream!
For the soul is dead that slumbers, And things are not what they seem.
Life is real!
Life is earnest!
And the grave is not its goal;
Dust thou art, to dust returnest, Was not spoken of the soul.
—Henry Wadsworth Longfellow (emphasis added)
Henry Wadsworth Longfellow remains one of the great American poets. The quote above is taken from “A Psalm of Life”. For the author who wrote “Hiawatha”, “Paul Revere’s Ride”, and many others, it’s tough to pick a favorite. But at this time of year, “Christmas Bells” is certainly my choice, especially in the hauntingly beautiful, and then triumphant, version set to music by contemporary band Casting Crowns.
Yet, I digress. What I really want to talk about is the phrase emphasized in the quote above: “…and things are not what they seem.”
We have already started reading articles in major and minor outlets about the “First Five Days” Indicator (a full description is below). And things are not what they seem. Even in its “best” version as described by Ryan Dietrich of LPL (again – more detail is below), this indicator is just cocktail party fodder. Don’t pay it any attention!
Soon, many market watchers and analysts will be looking at the well-known “First Five Days” indicator, which has been popularized by Yale Hirsch’s Stock Trader’s Almanac.
For the record, I think the Almanac contains a wealth of useful information. I keep one on my desk and give them out occasionally as Christmas gifts to friends and family. The “First Five Days” in January indicator holds loosely that the direction of the first five trading days of the year is a valid predictor of the direction of the market for the remainder of the year.
As proof of the indicator’s effectiveness, its proponents look back to 1950 and state that of 46 “First Five Days” that finished up, the stock market finished up in 38 of those years – an impressive 82.6% win rate for the predictor (though it did have an 89% win rate just 13 years ago…).
The indicator has been cited by such venerable sources as The New York Times, U.S. News & World Report, CNN, and Money Magazine. The problem is this: In the simple incarnation presented, it’s a useless indicator, or worse, it’s potentially dangerous to your wealth.
Well over a decade ago, I wrote in this same space that the “First Five Days” indicator is a bunch of bunk. I’ve read and heard so much about it again this year in blogs, on CNBC and even in the Wall Street Journal that I thought it would be useful for us to revisit this persistent myth.
At the core of human nature is the desire to understand complex systems in simple terms. The problem is that we tend to apply this simplistic cause and effect model to very intricate problems and expect similar “easy-to-understand” answers.
One good example is the Groundhog Day Indicator. Like the financial markets, weather systems are complex and difficult to predict. But we have devised many simplistic ways to predict the weather, including the infamous groundhog, Punxsutawney Phil. If he sees his shadow on February 2, there will be six more weeks of winter weather.
Because we like simple explanations, we are more than willing to believe cause-and-effect explanations that really don’t make logical sense. And in case you’re wondering, Punxsutawney Phil has been predicting weather since 1887, and has been correct around 39% of the time.
We just plain like simple answers. Maybe that’s why there are so many stock forecasting tools that use shaky logic and even shakier statistics to predict what will happen in the market in the days and months to come.
So, let’s look at one of the most hyped indicators this week.
Don’t Waste Your Time on This Meaningless Myth
Let me be blunt. The “First Five Days” indicator is the lowest form of analysis. It is the opposite of cause of and effect. This is the type of analysis that looks for any cause or correlation to tie to an end effect, regardless of logic, and as we shall see, regardless of statistical support.
The indicator is no more valid or useful than predicting the stock market based on Super Bowl winners or groundhog shadows. Here are three reasons why.
1. The logic is arbitrary. The raw numbers for this indicator show that the market has gone down during the first five days of January 31 times in the last 71 years. In those 31 occurrences, the market finished the year up 15 times and down 16 times.
So, the authors conclude that the indicator has no predictive value if it starts out to the downside. Looking at the same data, they like the results if the market starts out to the upside where it has “been right” 82.6% of the time. This is really just “markets go up more often than they go down” logic. And that’s not useful for me.
If the data do not fit our hypothesis, then change the hypothesis to fit the data. This is classic “curve-fitting” mentality. Do you want to risk any of your money based on that logic?
2. The triggering event is not statistically significant. For this indicator, all you need to trigger a yearlong market prediction is any up-move for five days. This means that trivial moves in the market could shape your outlook for the coming year.
Suppose after five days the market was up only one-quarter of a point. This would still trigger the indicator’s prediction for an up year.
What’s the problem with having a move of any magnitude trigger an indicator? A tiny move doesn’t tell us anything about what the market is doing. A small move either up or down is just random. It’s just part of the background “noise” of the market.
So, how do we decide what is meaningful and what is just background noise? One measure that many analysts use is the average volatility of a price movement. Long-time readers know that I use the Average True Range (ATR) of price as a measure of volatility. (In simple terms, ATR measures the average size of the daily range – the high minus the low – while accounting for gaps between bars.)
If we looked at the ATR for a five-day move, we would want our trigger to move up or down at least half of the average. Anything less would almost have to be considered random.
With that in mind, your industrious writer dug deep into the details of the “First Five Days” indicator’s raw data. I calculated the S&P 500 index’s ATR during the first five days for a 25-year chunk of time and checked to see how many of the “First Five Days” trigger signals could be considered more than random. The answer: Only seven!
And as a useful follow-on to this thought of finding a significant move, last year Ryan Detrick of LPL Financial provides us with this interesting data, looking only for years out of the last 70 where the S&P is up more than 1.5% for the First Five Days:
Here, Detrick is only looking for up moves >+1.5% and finds just 22 out of the last 72 years! While the returns seem very strong, it is once again a cherry-picked data set that is quite small.
3. Lastly, the sample population is too small. When we eliminate the trigger signals that are mere noise, we are left with less than two dozen triggers of the indicator over the last 72 years. This is not a statistically significant sample to base any predictions on, and this indicator is uncovered as just some simplistic curve-fitting that doesn’t mean a thing for traders and investors.
There is plenty of good analysis (including lots of good seasonal analysis) for you to use to help guide your trading and investing decisions. So, it makes a lot of sense to throw out the overly simplistic, statistically meaningless ones like the “First Five Days” indicator.
Here is one last note of caution. The indicator worked well the last two years. This brings another psychological bias into play: recency bias. We tend to assign an excessive amount of meaning to the most recent data points. Don’t fall into this trap with the “First Five Days” indicator.
You can still use it for cocktail party discussions, but don’t waste any money trying to use it to help you make sense of the markets.
As always, I love to hear your thoughts. Send them to drbarton “at” vantharp.com
Great trading and God bless you,
D. R.