U.S. Steel (X) facing resistance ahead of earnings report

U.S. Steel (NYSE: X) is scheduled to report second quarter earnings results after the closing bell on August 1. Analysts expect the company to report earnings of $0.39 per share after reporting $1.46 in the second quarter of 2018. The decline in earnings has caused a sharp decline in the stock over the past year.

If we look at the weekly chart, we see that the stock peaked up around $47.50 in February 2018. Since then the stock has moved sharply lower. If we connect the high from February with the high from last July, it creates the upper rail of a trend channel and the stock is approaching the upper rail at this time.

We see that the weekly overbought/oversold indicators haven’t been in overbought territory since the beginning of 2018. The indicators are approaching the same levels they hit in February before the stock rolled over and fell another 50%.

The Tickeron Trend Prediction Engine generated a bearish signal for U.S. Steel on July 23 and that signal calls for a drop of at least 4% within the next month. The signal showed a confidence level of 68% and past predictions for the stock have been successful 89% of the time.

In addition to the expected decline in earnings, the company’s profit margin is well below average at 6.7%. Given these fundamental statistics and the downward trend in the stock, it will be difficult for U.S. Steel to move higher in the coming months.

Contributor

Harry Richardson|Expert

Harry Richardson — Algorithmic Trader & Strategy Developer Harry is an algorithmic trader specializing in impulse and breakout trading strategies across cryptocurrency and equity markets. With more than 10 years of experience in developing automated trading systems, he focuses on building structured algorithms designed to capture momentum while maintaining strict risk control. His approach combines quantitative analysis, real-market execution, and continuous performance monitoring. Vitalii prioritizes risk management, drawdown control, and strategy stability over short-term optimization, ensuring algorithms are adaptable to changing market conditions. He has developed and tested hundreds of automated strategies, working extensively with live trading environments, forward testing, and portfolio-level algorithm management. His work centers on transforming trading ideas into fully operational, scalable automated systems.