Tesla Stocks (TSLA) Price Target Revised Amid Robotaxi Anticipation

Wednesday, 9 October 2024, 15:02

Price target revisions for Tesla stocks (TSLA) have arisen as the company prepares for its pivotal Robotaxi event. Analysts express mixed sentiments concerning the impact on TSLA shares amidst delivery reports showing shaky performance. As the stock hovers around $245, the upcoming event's success is crucial for its market standing.
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Tesla Stocks (TSLA) Price Target Revised Amid Robotaxi Anticipation

Price Target Revisions in Context of Tesla's Upcoming Robotaxi Event

Despite the recent popularity of Tesla's electric vehicles, analysts are revising the stock price target for TSLA as it heads into a critical moment—the highly anticipated Robotaxi event on October 10.

Tesla's Market Turbulence

Following the delivery report released on October 2, Tesla's shares experienced notable volatility, exacerbated by a year-to-date decline of 1.15%, stalling at $245.18.

  • RBC Capital maintains a 'buy' rating while adjusting the price target from $224 to $236, highlighting the potential for substantial revenue.
  • Oppenheimer's analysts predict the technology presentation will appeal to both bulls and bears, albeit with cautious outlooks.
  • Cantor Fitzgerald keeps a 'neutral' stance while increasing its price target, aligning predictions with recent production strength.

Concerns from Key Analysts

Conversely, bullish sentiments from some analysts are countered by skepticism. Notably, Gordon Johnson of GJL Research foresees disappointment at the Robotaxi event, citing several factors: high-profile departures, performance lag in FSD mileage relative to competitors, and potential technology limitations tied to current Tesla systems.

Ultimately, as TSLA edges closer to this crucial event, the interplay between optimistic forecasts and cautious analyses will shape the stock's trajectory.


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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