We’re in San Francisco at the NIRI meeting, warming up with winter coming to Denver and as summer carries airily on in stocks.
What metrics do you use to evaluate your own shares, investor-relations folks, or ones you own, investors?
I don’t mean fundamentals like cash flow, growth, balance sheet data. Those describe businesses. Stocks are by and large products.
If you bristle at that assertion, it’s just math. JP Morgan and Goldman Sachs have either outright said or intimated that about 10% of their trading volumes come from fundamental investment (our data show 13.5% the past five days). Implication: The other 90% is driven by something else.
This disconnect between how investors and public companies think about stocks and what sets stock prices is to me the root of the struggle for stock pickers and IR professionals alike today.
For instance, the winds are starting to whip around the regulatory regime in Europe called MiFID II, an acronym profusion that considers securities “financial instruments” and will dramatically expand focus on data and prices – two things that power short-term trading.
For proof, one expert discussing MiFID II at TABB Forum said derivatives are “ideally suited” to the regime because they’re statistical. And a high-speed trading firm who will remain anonymous here because we like the folks running it sees MiFID II as a great trading opportunity.
Back to the question: What are your metrics? It might not be what you’re thinking but it appears to me that the metrics most widely used by investors and companies to evaluate stocks are price and volume. Right?
But price and volume are consequences, not metrics. Think of it this way: What if meteorologists had gone to Puerto Rico and surveyed the damage and reported back that there must’ve been a hurricane?
That’s not very helpful, right? No, meteorologists forecasted the storm’s path. They offered predictive weather metrics. Forecasts didn’t prevent damage but did help people prepare.
The components of the DJIA are trading about 27 times earnings, as I wrote last week. Not adjusted earnings or expected earnings. Plain old net income. It’s a consequence of the underlying behaviors.
By understanding behaviors, we can prepare, both as investors and public companies, for what’s ahead, and gain better understanding of how the market works today.
I can summarize fifteen years of studying the evolution of the US equity market: machines are creating prices, and investors are tracking the averages. That combination creates valuations human beings studying businesses would generally find too rich.
How? Rules. Take MiFID II. It’s a system of regulation that advantages the pursuit of price based on market data, not fundamentals. In the US market, stock regulations require an intermediary for every trade. That also puts the focus on short-term prices.
Then every day by the close, all the money wanting to track some benchmark wants the best average price. So short-term price-setters can keep raising the price, and money tracking averages keeps paying it. It’s not a choice. It’s compliance.
In the past five days, data show the average spread between intraday high and low prices is a staggering 3%. Yet the VIX spent most of that time below 10 and traded down to 9!
How? Machines change prices all day long, and at the close everything rushes to the average, so the VIX says there’s no volatility when volatility is rampant. Since machines are pursuing the same buy low, sell high, strategy that investors hope to execute save they do it in fractions of seconds, the prices most times end higher.
But it’s not rational thought doing the evaluating.
The lesson for IR folks and investors alike is that a market with prices set this way cannot be trusted to render accurate fundamental evaluation of business worth.
What causes it to break? Machines stop setting prices. What causes that? There’s a topic for a future edition! Stay tuned.
