Alphabet Earnings Unlock 3 Dirt-Cheap AI Stocks! - Don’t Miss This Once-In-A-Lifetime Opportunity

The outlook for Micron stock has changed significantly. This video is based on extensive research and combines verified financial data, specific numbers, industry developments, and commentary from prominent Wall Street experts. I will present the evidence step-by-step and explain how it supports my central investment thesis. Listen carefully and watch the complete analysis to understand the full argument. Alphabet's latest earnings report confirms that fear of the AI investment cycle reaching its peak are overblown. The central thesis remains firmly intact. Demand for AI infrastructure, especially memory, is accelerating while supply constraints are becoming even more severe. According to Bank of America, hyperscalers are paying 35 to 40% of their capex directly to memory companies like Micron. In this video, I will discuss three stocks that have become deeply undervalued following Alphabet's earning report. Although I hold a master's degree with a specialization in finance, I am not a certified financial analyst or licensed financial advisor. This video is intended for informational and entertainment purposes only. Please conduct your own due diligence before making any investment decision. However, I will try to explain how to determine whether a stock is undervalued relative to its competitors and the broader market. Now, let's get to the most important point. Alphabet delivered excellent earnings, yet its stock fell approximately 6% the following day. That market reaction deserves a separate analysis, which I will cover in another video. For today's discussion, the critical development is Alphabet's capital expenditure guidance for the remainder of this year and its spending outlook for 2027. During the earnings call, Alphabet CFO Ananth Acharya said, "We are updating our full-year 2026 capex guidance range to 195 billion to 205 billion. As we previously shared, we continue to expect our CapEx to increase significantly in 2027. Listen to that final sentence again. We continue to expect our CapEx to increase significantly in 2027. Alphabet is not signaling a slowdown. It is preparing to spend substantially more next year. The CFO also confirmed that existing supply cannot meet the company's immediate requirements. Given the supply constrained environment, we plan to spend the use of third-party capacity in Q3 as a bridging strategy. However, it will create modest margin pressure in the near term. That statement validates my thesis. Alphabet is not turning to third-party capacity because demand is weakening. It is doing so because demand is growing faster than infrastructure can be delivered. This creates a major opportunity for companies supplying memory, computing capacity, and other critical AI infrastructure. Micron is the main beneficiary here because ever-increasing memory prices are the main reason these CapEx continue to rise every quarter. Bank of America analyst Vivek Arya argues that memory now accounts for approximately 35 to 40% of cloud AI capital expenditures, two to three times its historical share. Even Microsoft acknowledged the severity of this problem in its latest earnings report. Of the company's planned $190 billion in capital expenditures, approximately $25 billion is attributable to higher component prices, meaning inflation and severe supply shortages across the hardware industry have forced Microsoft to spend an additional $25 billion to acquire essentially the same amount of physical equipment. Components refers to physical hardware required to build and operate massive cloud computing and artificial intelligence data centers. This includes memory processors networking equipment, storage systems, power management hardware, and cooling infrastructure. Industry analysts expect the pressure on memory prices to continue. UBS analyst Nicholas Godo raised his base case forecast for DDR contract price growth to 32% quarter over quarter, substantially above his previous estimate of 17%. He also increased his fourth quarter forecast from 12% to 18%. UBS now expect memory industry revenue to reach 992 billion this year and to 1.76 trillion in 2027. The firm described the recent pullback in memory stocks, which have declined by an average of approximately 17% from their June peak, as likely temporary. Wall Street's average price target for Micron now stands at 1,507, implying approximately 52% upside. This unusually low 361 price target reflects analysts who have not yet updated their models following Micron's latest earnings, guidance, and long-term customer agreements. Major firms have already raised their target prices substantially. JP Morgan moved to 1,540, Morgan Stanley to 1,200, and most notably, Susquehanna to 2,000, with the highest target reaching 2,200. The updated institutional outlook is significantly more bullish than the low end of the range suggests. If you look at the P/E ratio and profitability comparison, Micron is at dirt cheap forward P/E ratio of six while having a superior profitability profile as compared to its industry peers. The second stock that became significantly undervalued following Alphabet's earning report is Nvidia. Even the CEO of GMO, the investment firm co-founded by renowned market bear Jeremy Grantham, had described Nvidia as one of the biggest opportunities in the market today. That endorsement is especially notable because GMO is widely known for its valuation discipline and cautious approach to high-growth stocks. Based on earnings estimates, Nvidia looks remarkably cheap heading into 2027, trading at just 16 times forward earnings. Opportunities this attractive among blue-chip stocks are rare in today's richly valued market. Why has Nvidia become so inexpensive? The clearest explanation is that investors have shifted their attention toward the memory bottleneck trade. However, there is no doubt that Nvidia remains the undisputed king of AI infrastructure. Nvidia should be valued on its earnings power and future growth. Based on those metrics, describing the stock as overvalued or expensive is no longer justified. At a share price of 207, Nvidia trades at approximately 23 times earnings. That multiple is below the semiconductor industry average of 24.5 and represents only about half of Nvidia's 5-year historical price-to-earnings ratio of 43 times. In other words, the company's valuation multiple has compressed by nearly 50% even as the underlying business has roughly tripled in size. The valuation becomes even more compelling after adjusting for expected growth. Nvidia's forward price-to-earnings-to-growth or PEG ratio stands at just 0.5 compared with a sector median of approximately 1.32. A PEG ratio below one generally indicates that market price does not fully reflect the company's projected earning growth. Analysts expect Nvidia to generate earnings per share of 8.99 in fiscal 2027, increasing to 12.87 in 2028, and approximately 15.98 in 2029. Although annual EPS growth is forecasted to moderate from roughly 88 to 43% and eventually to 24%. The company will still be producing substantial double-digit growth from an increasingly large earnings base. If these forecasts are achieved, Nvidia's forward PE ratio falls from approximately 23 for fiscal year 2027 to 16 in 2028 and to just 13 in 2029. This means the stock becomes progressively cheaper as earnings expand even without assuming a higher share price. Wall Street's average price target currently stands at 302 implying approximately 45% upside from the current price. Analyst targets range from 180 to 500 reflecting unadjusted certainty about growth, competition, and future AI spending. Current price suggests the downside is limited. Nevertheless, the consensus remains clear. Nvidia continues to deliver exceptional earnings growth while its valuation has compressed to levels below both its industry and historical averages. The stock's current valuation reflects far more caution than its headline reputation suggests. Third stock that has become extremely cheap after Alphabet's earning announcement is Navis. Alphabet's latest earning call strengthened the investment case for specialist AI cloud providers. Despite planning to earn billion in 2026 capital expenditures, Alphabet acknowledged that its internal infrastructure cannot satisfy client demand. CFO Anat Ashkenazi said the company would expand its use of third-party capacity in the third quarter as a bridging strategy while it builds additional internal capacity. This statement does not confirm that Alphabet will become a Navis customer. However, it validates the market Navis is pursuing. If a company with Alphabet's capital resources, proprietary GPUs, and enormous data center footprint still needs external capacity, then smaller AI laboratories and enterprise face an even greater infrastructure challenge. They lack the time, expertise, and capital required to secure power, construct data centers, and assemble large GPU clusters independently. Navis offers those customers immediate access to purpose-built AI infrastructure. Unlike traditional clouds originally designed for general computing, its platform was designed specifically for AI workloads. The company is also moving beyond basic GPU rentals by building a software layer for training, inference, agentic AI, and physical AI. This creates additional monetization opportunities and strengthens customer integration. Its relationship with Nvidia provides another strategic advantage. Nvidia invested 2 billion in Nebius and is supporting its plan to deploy more than 5 gigawatts of Nvidia-powered capacity by the end of 2030. The partnership covers AI compute pre-design, early access to new architectures, inference software, and fleet management. This backing improves Nebius' ability to deploy advanced systems quickly in a market where hardware access and technical execution remain major bottlenecks. Nebius has also demonstrated that large customer contracts can unlock financing. Its first $775 million secured debt facility, combined with cash flows from associated customer agreements, cover more than 100% of capital expenditure required for the underlying GP infrastructure. This creates a repeatable model. Win a large contract, finance the corresponding asset against predictable customer cash flows, and use the resulting capacity to serve additional customers. Existing agreements with Microsoft and Meta further validate demand for Nebius' infrastructure. However, the opportunity remains accompanied by substantial risk. Nebius is still scaling rapidly, requires considerable external capital, and is not expected to generate positive free cash flow in the immediate future. Construction delays, GPU shortages, debt costs, customer concentration, and pricing competition could materially affect returns. The stock's recent decline of more than 40% demonstrates its sensitivity to changes in the market sentiment. Nevertheless, Alphabet's decision to rent third-party capacity reveals the central AI bottleneck. Demand is growing faster than internal infrastructure can be delivered. Nebius is positioned to sell the scarce resource the industry needs urgently. Ready-to-use large-scale AI computing capacity. If management executes effectively, today's capacity shortage becomes Nevis' long-term growth engine.