Make sure clients don’t take the wrong lessons from the drop

Financial advisers and their clients deserve a pat on the back for their response to the recent, dramatic market volatility.

Advisers have counseled their clients not to panic in market downturns and to invest for the long run, and, according to reports, most clients have heeded that advice. Those who became nervous reached out to their advisers for reassurance, and, for the most part, were comforted.

The next job for advisers is to make sure clients don’t take the wrong lesson from this experience: That market corrections always reverse themselves quickly and are therefore buying opportunities. Just as they shouldn’t rush to sell in a correction, they should not rush to buy when the correction appears to have ended. Thoughtful evaluation is the key in both situations.

The stock market does not always bounce back quickly, and during corrections there can be many false bottoms. In case they have forgotten, the market plunged more than 50% from October 2008 to March 2009, and then took more than three years for it to get back to the October 2008 level.

The causes of this drop will likely take some time to diagnose, but the speed of the market’s advance in 2017 and so far in 2018 certainly contributed. Market observers had been warning for some time that it was overdue for a correction, and some argued stock prices were ahead of company earnings, meaning many companies were overvalued.

(More: Robo-adviser websites crashed as market slid)

Luckily, the preliminary evidence suggests that most individual investors stayed calm and did not rush to sell. The relatively low trading volumes during the correction is the evidence.

The initial diagnosis is that some high-tech new products, if they didn’t trigger the fall, contributed to its pace and depth, much as portfolio insurance contributed to the pace and depth of the 1987 correction.

According to Bloomberg News, key suspects are two exchange-traded products that bet that market volatility would remain low, and when it didn’t, resulted in selling by the institutions offering the products.

Other suspects are computer-driven program trading where sell orders are triggered by market movements. Once the market declines a programmed amount in a given period, the computers sell a certain number of shares. If the market continues to decline, the computers sell more shares. The result can be a downward spiral.

The biggest question is what caused the volatility to initially spike enough to trigger the volatility-related ETNs and the computer-driven portfolios to sell?

Corporate earnings, on average, have been strong, though Apple’s were mildly disappointing. All economic indicators are positive, with strong GDP and employment numbers. There was a mild increase in inflation and 10-year Treasuries hit 2.8%, but these seem unlikely to prompt such a sudden and deep sell-off.

No matter what the postmortems on this correction show to have been the proximate trigger, there are lessons that can already be learned.

First, investors must be aware that corrections can occur, even when all the economic and financial indicators seem positive. This is a lesson advisers should reinforce to their clients.

Second, while it’s possible to anticipate that a drop will occur, it’s impossible to know exactly when and what might trigger it. Some market commentators have been predicting a correction for more than a year.

(More: 10 worst days ever for Dow Jones)

Third, the correction has provided another opportunity for advisers and clients to test the clients’ real risk tolerances. Just as markets never go straight up, they rarely go straight down in a correction. There are usually false bottoms that can invite investors to buy apparent bargains, only to be hurt by another down leg — or two. They also rarely recover in a straight line. This makes market-timing a dangerous tactic.

Advisers should continue to reinforce to clients that a well-designed, long-term investment strategy — with an asset allocation matched to their needs and risk-tolerance — is the best approach.