In the stock market, uncertainty and volatility go hand-in-hand, and the COVID-19 pandemic has turbocharged both this year. This is leaving investors asking what tools they can use to analyze data and accurately predict future corporate earnings.
- The COVID-19 pandemic has caused economic uncertainty and market volatility. This is making it difficult to forecast corporate earnings.
- Investors need to use the right tools to manage risks concerned with corporate earnings. StarMine’s SmartEstimate and Predicted Surprise are part of Refinitiv’s regular earnings season forecast publications, alongside detailed I/B/E/S Estimates.
- Many companies have withdrawn earnings guidance. The algorithms used in SmartEstimate and Predicted Surprise can help investors resolve this challenge.
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COVID-19 has had a severe impact on global markets.
The Dow Jones Industrial Average, for example, has fluctuated since the start of the year. On 5 February, the market index closed at a record high of 29,276. About five weeks later, on 18 March, it closed at 20,704, a loss of 29 percent.
Five months later, the index stands at 28,645 (as of the close on 1 September) — and we are only eight months into the year.
Anticipating corporate earnings
The effect of the health crisis on the economic and investment landscape is making a mess of the art of correctly anticipating corporate earnings.
To remedy this problem, it’s essential to use the right tools. StarMine’s SmartEstimate and Predicted Surprise form the basis of Refinitiv’s regular earnings season forecast publications, alongside detailed I/B/E/S Estimates.
Rarely have these analytics been more useful and accurate. In managing risk, they are especially helpful during earnings season as investors try to anticipate which companies might disappoint.
StarMine’s SmartEstimate and Predicted Surprise
The SmartEstimate is a weighted average of analyst estimates, with more weight given to more recent estimates and more accurate analysts.
Our studies have shown that when the SmartEstimate differs significantly from the consensus (I/B/E/S Mean), the Predicted Surprise accurately predicts the direction of earnings surprises or further revisions 70 percent of the time.
When significant Predicted Surprise for revenue is also present for the period, the accuracy improves to 78 percent.
Each quarter, we predict five companies to beat and five to miss when they report earnings results. We do these for each of our three major regions.
For Q1, we got 90 percent directionally correct for North America. For FY 2019, we had 100 percent directionally correct in UKI/Europe, and 80 percent in Asia/Pac. And, in Asia, 100 percent of those we predicted to miss expectations actually did.
Earnings in Europe
For UK, Ireland and Europe, we correctly picked Amadeus IT Group, Boohoo Group, Hapag Lloyd, Laboratorios Farmaceuticos ROVI, and William Hill to beat earnings estimates.
On the disappointing side, we correctly chose 1&1 Drillisch, Antofagasta, K&S, Renault, and Eni.
Earnings in North America
In North America, our 90 percent score included earnings winners PennyMac Financial Services, Humana, Clorox and Eli Lilly. We scored 100 percent on earnings laggards Navistar International, Capri Holdings, Ford Motor, Sabre, and Cinemark Holdings.
Earnings in Asia
Looking at Asia, our winners included China Conch Venture Holdings, Q Technology, and YiChang HEC ChangJiang Pharmaceutical. We correctly predicted that these companies would provide disappointing earnings: Cathay Pacific Airways, China Southern Airlines, ASM Pacific Technology, Shenzhen Inovance Technology, and Catcher Technology.
Withdrawal of earnings guidance
Many companies have withdrawn earnings guidance and a significant minority of sell-side analysts appear hesitant to stick their necks out during this period of uncertainty.
The result is a large percentage of stale estimates in aggregate, equal-weighted averages. This leaves the buy-side increasingly left to its own devices when trying to anticipate earnings surprises.
The StarMine SmartEstimate, Predicted Surprise, and I/B/E/S Estimates can help with this challenge.
Since those algorithms automatically overweight the analysts brave enough to make meaningful recent revisions to their outlooks and company experts who have proven to be more accurate than their peers, they may be more valuable tools now than ever before.