Company-driven activity is distorting your share price – but you’re not helpless, says James MacGregor
Computer-driven trading and investing programs now account for more than three quarters of the daily trading volume on both the NYSE and NASDAQ. To which many companies respond: ‘So what? That means lots more buyers and sellers for our shares, and the market price is still the market price. And even if it was causing a problem, there’s not much we could do about it. Right?’
Well, no, not right at all. All that computer-driven activity can – and does – seriously distort the price of a company’s shares. When that happens, the conventional investors that are a company’s best IR prospects may reduce their estimates of what a firm is worth, or simply ignore the company until the computer-driven distortion lessens. We see both reactions quite often.
The good news is that there are now tools that enable companies to see the degree to which computer-driven trading is influencing their share price. And there are now various IR strategies that can be applied to mitigate high-algorithmic influence, or to take advantage of low-algorithmic influence.
First, here’s why there’s a problem: computer-driven models very often pay no attention to a company’s business performance, financial condition or future prospects. Securities analysts and portfolios are rarely unanimous when valuing these parameters, but they’re usually in the same ballpark. The algorithms, looking at vastly different metrics, may be miles away from the ballpark. By sheer volume, they can – and do – drag share price some distance away from the conventional investors’ range of valuations.
Optimally, there is a self-correcting mechanism available. Computers are great at dealing with price, less so with value. When there’s a substantial trade between a couple of major asset managers, many algorithms pick it up and make that price the new zero point for trading strategies involving the shares in question. But asset managers’ trading desks read the same data. Their traders and portfolio managers may decide the algorithmic distortion of price is a risk factor that requires a step down in valuation. So: buy lower, sell sooner. Or portfolio managers may decide the algorithmic distortion risk is so great that the shares should be ignored, certainly in the near term, perhaps longer.
Enter gamma, which measures the degree to which a firm’s share pricing is influenced (and perhaps distorted) by computer-driven trading/investing programs. Gamma of 90 percent or higher shows a stock substantially free of algorithmic influence. Gamma of 70 percent or less shows a stock heavily influenced by computer-driven trading, and thus one that otherwise excellent investors may devalue or take off their target list.
Gamma was developed by Denver-based ModernIR, and is now being applied by a sizable number of savvy IR departments (full disclosure: our firm was part of gamma’s conceptualization). Gamma awareness leads to three strategic activity areas:
- Take actions that calm algorithmic energies and avoid actions that ramp them up. Positive example: give quarter-in-progress earnings guidance. Negative example: don’t make major financial announcements on days when your options are being repriced
- If gamma has recently dropped to unacceptably low levels, conventional investors are probably sitting on the sidelines in response to an influence that may not be company-specific. Identify the issue and address it in investor communications. Several investors specialize in this sort of transitional situation so get to know them before you need them. If gamma has been at unacceptable levels for some time, however, there’s a larger performance or communications issue that needs to be sorted out
- If gamma is particularly high, the perception of investors that actually know the company is driving market price. If that price is where the company thinks it should be, the prevailing IR strategy needs no tinkering. But if the untainted-by-algorithms price is lower than it should be, this is a prime moment for outreach to investors that have shown interest but haven’t committed.
The gamma trend may be new, but one observation remains true: companies are most vulnerable to computer-driven share price distortion when they tell their story badly or let their relationships with key investors atrophy. First-quality IR remains a weapon against undue algorithmic influence.
James MacGregor is co-founder of Abernathy MacGregor
This article appeared in the summer 2015 print issue of IR Magazine