By Thomas Kostigen
We hear a lot about which stocks to buy—the latest, greatest, new, new thing that is setting Wall Street afire and has investors eager to buy shares because prices are going up, up, up. But what about which stocks to sell? Of course, selling is just as important as buying when it comes to investing. Just ask any hedge fund manager who was short GameStop this month, or the commodity silver and was caught holding those positions when prices soared unexpectedly.
So how does the average investor know when to sell, or better yet which stocks and sectors to avoid?
A good financial advisor can tell you what dangers may be around the corner that could crash a company’s share price. He or she should be analyzing short positions—how many investors are betting a share price will go down—as well as analysts’ consensuses about earnings that, in turn, can affect share price.
Still, externalities can be tricky to assess, mostly because they are unknown and/or unexpected…right? After all, you couldn’t predict, say, an oil tanker accident that creates a spill and sends that oil company’s share price lower. Or a pandemic’s impact on a live event company’s revenue. Or a contamination issue with a food company that makes earnings go bust.
But you could help mitigate those risks by utilizing filters for your portfolio. That means deciding upfront and before you purchase a stock whether or not it fits with your holding criteria. These “negative filters” are commonly used by fund managers. Managers hold themselves accountable to “universes” of stocks that they have vetted and monitor and consistently watch for entry opportunities. This allows them to avoid entire sectors that may be vulnerable to downswings. These macro filters are requisite for professional money managers and they should be incorporated into individual investors’ tactics, too.
Filters help with avoidance. Selling, on the other hand, requires a different strategy.
Artificial intelligence is playing its part in sell decisions by instituting automatic alerts for investors based on myriad factors that allow machines to “forecast” happenings. These are based on algorithms that track the likelihood of negative events.
There are more than a dozen companies that leverage technology to figure predictive trading patterns. The risks monitored range from compliance issues to trading volume to financial statements. IBM technology is even being used to monitor social media posts and news articles to assess the impact on stocks. Exchange-traded funds and other vehicles are being built around advanced AI.
Predictive analysis is where things get really interesting. Police departments are using predictive analysis backed by AI to figure when and where crimes may happen —ahead of them occurring. It sounds a bit like the film Minority Report, but it’s not science fiction; its science based. The likelihood of an event happening is assessed a certain score. These scores, can then be assigned a weighting. We often call this weighting “chance.”
Taken into the investment markets, chance can be greatly reduced by AI. Predictive patterns can be discovered and millions of scenarios assessed by super computers. The result could be a sell alert for investors. It may not be perfect, but it’s nearer to certainty than manual assumptions. The same technology can also determine which investment sectors to avoid.
A quick internet search will easily provide you a list of companies incorporating AI into their operations. Many of them offer their services to retail investors.
Besides AI, there are other ways to help you know when to sell or avoid certain companies. We’ll discuss the promise of three-dimensional sustainable finance next week.
Thomas Kostigen is a contributing writer to MyPerfectFinancialAdvisor, the premier matchmaker between investors and advisors. Thomas is a best-selling author and longtime journalist who writes about environmental, social, and governance issues.
