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These 2 Auto, Tires and Trucks Stocks Could Beat Earnings: Why They Should Be on Your Radar

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Corporate EarningsAnalyst EstimatesAnalyst InsightsCompany FundamentalsAutomotive & EV
These 2 Auto, Tires and Trucks Stocks Could Beat Earnings: Why They Should Be on Your Radar

Zacks Investment Research highlights its proprietary Earnings ESP (Expected Surprise Prediction) tool, designed to identify stocks likely to beat earnings estimates by comparing the Most Accurate Estimate to the Zacks Consensus. This methodology, when combined with a Zacks Rank #3 (Hold) or better, has historically predicted positive earnings surprises 70% of the time and generated average annual returns of 28.3% over a 10-year backtest. Applying this filter, the analysis points to Cummins (CMI) and Rivian Automotive (RIVN) as two "Auto, Tires and Trucks" stocks with positive Earnings ESPs, suggesting they are poised to exceed expectations in their upcoming August 5, 2025 earnings reports.

Analysis

The analysis centers on the Zacks Earnings Expected Surprise Prediction (ESP) model, a quantitative tool designed to identify companies likely to surpass earnings expectations. This model's efficacy is supported by a 10-year backtest showing that stocks with a positive ESP and a Zacks Rank of #3 (Hold) or better delivered a positive earnings surprise 70% of the time, yielding an average annual return of 28.3%. The report applies this methodology to the Auto, Tires and Trucks sector, highlighting two specific companies ahead of their August 5, 2025 earnings releases. Cummins (CMI) is flagged with a positive Earnings ESP of +5.46%, derived from its Most Accurate Estimate of $5.24 per share versus a consensus of $4.97. Similarly, Rivian Automotive (RIVN) shows a positive ESP of +5.82%, with a Most Accurate Estimate of a $0.62 loss per share compared to a consensus estimate of a $0.66 loss. Both companies currently hold a Zacks Rank of #3 (Hold), which suggests they are expected to perform in-line with the broader market, but the positive ESP metric indicates a statistical likelihood of them posting better-than-expected bottom-line results.

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