Will the downtrend continue for Fossil Group (FOSL)?

Fashion retailer Fossil Group (Nasdaq: FOSL) has been trending lower since hitting a 52-week high in June. The downward trend has been rather well organized and a trend channel has formed that defines the various cycles within the overall trend. The stock is close to the upper rail of the channel at this time.

We also see that the upper rail is in close proximity to the 50-day moving average and that trend line could act as an additional layer of resistance. The daily stochastic readings are close to overbought territory and did just perform a bearish crossover.

The Tickeron AI Prediction tool generated a bearish signal on Fossil on March 1. The prediction had a confidence level of 70% and previous predictions have been correct 75% of the time.

Fossil’s fundamentals are somewhat mixed. The earnings have been flat over the last three years, but they jumped by 58% in the most recent earnings report. Sales have declined at a rate of 7% per year over the last three years and they were down by 15% in the most recent quarterly report.

The management efficiency measurements are below average as well. The return on equity is a paltry 3.6% and the profit margin is -0.1%.

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.