TipRanks

Wed, Jun 11, 2025, 6:30 PM6 min read

From a fundamental perspective, social media and technology juggernaut Meta Platforms (META) recently made a compelling case for long-term investment. Meta recently entered into a 20-year power purchase agreement with Constellation Energy’s (CEG) Clinton nuclear plant in Illinois. Primarily, the deal will help Meta manage its energy costs, a core component of its forward growth strategies.

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Indeed, artificial intelligence has emerged as one of the top priorities in the tech ecosystem. However, generative AI comes at a significant cost: substantial power consumption. In 2023, the power required to support AI deployment was estimated at 1 gigawatt. Experts believe that this rate will increase sevenfold to tenfold in the next two years, thus underscoring the criticality of Meta’s energy deal. I too am bullish on META, but for different reasons.

Market narratives aren’t always reliable indicators of future valuations. Even as sentiment around Meta remains largely optimistic, analysts are actively revising their forecasts. While the majority maintain a bullish stance, the consensus price target suggests a degree of caution.

For traders focused on near-term gains, compelling narratives alone don’t offer enough concrete data for decision-making. In these cases, speculators often rely more on empirical, quantitative indicators to inform their strategies.

When investors turn to financial publications, they’re not simply looking for recycled narratives—they’re in search of opportunities, specifically cases where the market may have mispriced certain stocks. To uncover these discrepancies, investors often turn to fundamental and technical analysis.

While these methods can provide helpful context and short-term guidance—helping frame potential entry and exit points—they fall short of offering true empirical precision. The core issue lies in the problem of non-stationarity: over time, the metrics and benchmarks used for analysis can shift significantly due to changing market conditions and sentiment cycles, undermining their long-term reliability.

For example, META stock recently closed near the $700 level. Five years ago, the equity could be bought for around $230. And a decade ago, META was priced at around $117. Attempting to conduct meaningful statistical analyses, such as price clustering, would be impossible given the significant disparity in share prices.