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On 16 July 2020, Analysts Dan Levy and AJ Denham from Credit Suisse raises Tesla Inc. (NASDAQ: TSLA) price target to $1,400 from $700.
Highlights from the original note:
" A Multitude of Favorable Factors for the Stock, We Believe Material Hiccup Could Lead to Correction: We see multiple factors responsible for the recent sharp run-up in euphoria(Tesla the most widely bought stock in the past month on Robinhood), covering by short sellers, and buying by quant / momentum investors. With the stock Priced for perfection, we believe any material near-term negative datapoint could lead to a drawdown.
Yet Positive Catalysts Ahead: 2Q EPS, Battery Day, an addition to the S&P 500, and further plans on capacity expansion. This latter point is crucial, as over the next 18 months Tesla capacity may nearly double from its current level (currently 700K, going to 1.3MN units). It potentially implies upside to 2022 volume estimates (we forecast -970K)
Bar is Raised, Now Clear It: Tesla is now the world's most valuable automaker even though it will only sell 450-500K units the year (<1% global volume). To justify the current stock price, we believe one must assume that by 2025 Tesla will sell 2.2MN units (making it as large as the German luxury brands), while trading at an elevated 30x+ PE multiple. It tells us that the onus is now on Tesla to execute to these lofty expectations; albeit, an elevated stock price provides Tesla with a significant cost-of-capital advantage.
We Raise Our Target Price to $1,400 (vs. prior $700), while also raising our Blue Sky scenario to $2,300 and our Grey scenario to $800. The primary driver is an increased volume outlook, as we now forecast 2025 volume of 1.8MN units vs. prior 1.2MN. Tesla's plans to expand capacity, alongside a competitive advantage and a brighter outlook for EV penetration, justiy the higher volume outlook. Our increased target price also reflects a slight improvement in our margin outlook, increased target multiples, and higher probability attributed to the Bull and Uberbull cases in our probability-weighted framework."
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