3 Stocks That Investors Can Buy That May Double in Value
Coinpedia
1h ago
Ai Focus
NVIDIA, Applied Digital, and Micron draw attention due to the expansion of AI expenditure cycles. The article states that NVIDIA is the strongest leader in AI, Applied Digital has higher speculative upside potential, and Micron benefits from the AI memory shortage; each of the three has different risk-return characteristics.
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3 Stocks That Investors Can Buy That May Double in Value

NVIDIA’s ( NVDA ) stock price is once again approaching record highs. With the accelerating demand for infrastructure driven by AI, analysts’ target prices remain significantly higher than the current stock price.

Applied Digital ( APLD ) achieved a year-on-year revenue growth of 322%, further consolidating its position as a high-growth AI data center target.

Micron (MU) has benefited from the shortage of storage chips driven by AI; a recent analyst has raised the target price for the stock to $3,000.

As the AI spending cycle expands in the fields of semiconductors, storage, and data center infrastructure, investors are increasingly looking for stocks that have the potential to double in value. NVIDIA, Applied Digital, and Micron attract a lot of investor attention because they each offer different ways to benefit from the rising AI demand. NVDA provides scale and profitability, while APLD and MU offer more aggressive upside potential. The key is whether their growth will continue to prove that the expectations already built into these stocks are reasonable.

NVIDIA ( NVDA ): There is still room for improvement for the leaders of AI

NVIDIA remains the strongest company in this group, but its focus has shifted from its early AI transactions to a story of substantial profit growth. On October 7th, the stock price closed at $237.47, near the 52-week high of $243.37. The stock has attracted significant trading activity, with over 81.7 million shares traded on the latest trading day. Its forward price-earnings ratio is around 19.6 times, and analysts maintain a consensus of "strong buy," with an average target price of $328.72.

The fundamentals remain strong. NVIDIA's quarterly revenue was approximately $96 billion, a year-on-year increase of 106%, of which data center revenue accounted for about $89 billion. As hyperscalers expand their AI infrastructure spending, analysts continue to raise their forecasts. For example, Needham has raised its quarterly revenue estimate to $109 billion.

NVIDIA has also extended its stock repurchase authorization to $235 billion by 2028, providing investors with another potential source to support earnings per share. The company's market value is approaching approximately $6 trillion, which means that even if it doubles again, there would still be a need for exceptional and substantial expansion in profits and valuation.

This makes NVDA different from the other two stocks. NVIDIA may still continue to show considerable upside, but a 100% increase is not the baseline expectation of analysts. Rather than calling it a potential double-digit performer, it would be more accurate to describe it as a high-quality AI leader, while APLD and MU offer more direct potential for doubling in value.

Applied Digital ( APLD ): Stocks of AI data centers that investors are concerned about

Applied Digital has become one of the more aggressive ways to invest in the infrastructure construction of AI. The stock closed at $23.81 on October 7th, down 6.04% after the financial report, but it returned above $24 during pre-market trading on October 8th. With a trading volume of nearly 48.8 million shares, it demonstrates how quickly investors' interest in this company has changed.

Revenue growth is the main reason that investors continue to pay attention to. Applied Digital reported revenue of $341.9 million, a year-on-year increase of about 322%, which is significantly higher than expectations. The company is expanding its data center layout to serve high-performance computing and AI customers, however, the losses are still quite substantial.

The imagination in the upper space is exceptionally vast. 15 analysts tracked by S& P Global have reached a consensus of "strong buy" for APLD, with an average target price of $64.57, representing a potential increase of about 171% from the closing price on October 7th. The highest target price reaches $93.

3. Micron (MU): The storage boom (AI) may continue to drive up the price of MU

Micron benefits from another aspect of the AI infrastructure cycle: storage. On October 7th, the MU stock closed at $1,088, up 4.06% during the session. Over the past year, the stock has appreciated by approximately 444%, but its forward price-earnings ratio is still close to 6.2 times due to the very rapid increase in earnings expectations. The average analyst target price is around $1,555, and the highest target prices have risen significantly.

The biggest catalyst is the tightening of the storage supply and demand relationship. AI Accelerators require increasingly high-bandwidth storage, and industry demand is expected to exceed supply until 2027 and 2028. This week, this view has become even more optimistic, as D.A. Davidson Analyst Gil Luria raised Micron's target price from $2,100 to $3,000. This is one of the most aggressive target prices on Wall Street at present, indicating a potential upside of over 175% from the latest closing price.

Which of these three stocks is most likely to double in value?

For investors looking for stocks that may double in value, these three stocks offer distinctly different risk-return profiles.

NVIDIA is the strongest business and also the most mature AI winner. However, to achieve a 100% increase, there still needs to be another significant expansion in profits or valuation. Applied Digital has the highest speculative upside potential, and its current analyst target price already suggests a possible doubling. Micron, on the other hand, boasts explosive profit growth and a structural AI storage shortage, giving it a credible long-term path towards the most aggressive target prices.

The opportunities are great, but so are the expectations. APLD has the highest potential for growth, MU boasts the strongest cyclical nature, AI features the best storage configuration, and NVDA remains the highest-quality investment target among them.

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