In the constantly fluctuating financial markets, the precision of reported figures can sometimes paint a misleading picture of stability and predictability. The penny-perfect prices you see one minute will probably change while you grab a cup of coffee or even blink.
From the minute-by-minute volatility of cryptocurrencies to more subtle stock-price moves and financial data reports, the exaggerated precision of financial data often belies the inherent volatility that defines these markets.
I swear, this is an important question. Let me save you some time and guard your long-term sanity with a couple of real-world examples.
Examples, please
At the time of this writing on the early East Coast morning of Feb. 7, Bitcoin (BTC -2.25%) is down by 0.70% in 24 hours. The price per token is $42,785.61. Oh, but wait -- Coinmarketcap's quote updates automatically. Thirty seconds later, I'm looking at a 0.80% price drop to $42,773.27. I will probably never see these exact prices again.
Rounding off to the nearest dollar per Bitcoin, the chance of seeing a repeated price increases exponentially. Using proper rounding technique, Bitcoin prices can move $21 higher or lower without changing the percentage reading at the precision of a single decimal point, or 0.1%.
You might call Bitcoin too volatile for this thought experiment. So let's look at a popular stock, instead.
Today, the first 20 pre-market trades in chip designer Nvidia (NVDA 6.18%) fell in a range between $704.00 and $704.28, with price differences as large as 0.02% between trades executed in the same second.
Oh, but Nvidia comes with a high stock price -- perhaps headed for a stock split someday soon -- and massive trading volume. Furthermore, the company is on a roll as a leading provider of accelerator chips for modern artificial intelligence (AI) systems.
Share prices more than tripled over the last year, with a gain of 230.33%. Nvidia's Beta value stands at 1.7, indicating a rather high level of volatility, compared to the S&P 500 broad market index. Hence, Nvidia prices are always on the move, and the quote is rarely stable beyond the decimal point separating dollars from cents.
You'll often see hypercorrect figures in financial metrics, too. I could look at the raw numbers in Booking Holdings' (BKNG 0.53%) latest quarterly report, for example, and calculate its year-over-year net income growth to four significant digits. But the travel-booking giant's management discussed the results in terms of 51% higher income, not 50.72%.
That's the right idea. Thanks, y'all.
The best reason for stock splits
This is one of the few reasons why stock splits aren't entirely pointless. When applied to a stock with share prices measured in thousands of dollars and equally lofty earnings per share, a quick stock split can simplify their financial picture overnight.
Take, for instance, Google parent Alphabet (GOOG 9.96%) (GOOGL 10.22%). Its Class A stock traded at $2,255.34 per share at the market close on July 15, 2022. One weekend and a 20-for-1 stock split later, Alphabet started the next Monday session at $112.64 per share.That's 0.1% below the last quote before the split.
As I said, this move actually simplified Alphabet's financial report somewhat. The company originally reported earnings of $27.26 per share in the second quarter of 2021, reflecting a 169% year-over-year increase. In Alphabet's first report after the split, one year later, the same result was presented at $1.36 per share, instead.
That level of not-so-granular detail is just easier to work with. And a bottom-line result that previously exceeded Wall Street's consensus estimates by $0.10 per share could now be exactly in line with the analyst target, instead, all thanks to coarser reporting and rounding effects.
It's not a game-changing difference, and I'd be fine with Alphabet's pre-split reporting, as well. But if you ever find yourself wishing for a stock split, you're probably facing a cumbersome amount of financial detail.
Yes, proper precision really matters
Yeah, I know. I'm getting all worked up over a silly little reporting quirk. The whole argument could be presented in an "Old man yells at cloud" meme.
But I really do take this stuff seriously. Overly precise data can send investors down a pointless rabbit hole where every decimal point looks important and needs an explanation. I give props to companies like Alphabet and Booking Holdings, with leaders who seem to appreciate the value of simpler reports. Surely you don't want to waste time on doing extra math at an irrelevant level of precision.
Simply noticing incredibly exact reports and estimates can be helpful in other ways, too. I can't take people seriously if they claim to know a particular company's revenue growth or the inflation rate in Slovenia or any other market prediction five years in the future with decimal-point accuracy. And in this era of AI bots everywhere, ultra-precise data points are often a giveaway unveiling an article that never saw a human review before publishing.
