Micro/Small Cap AI Stocks Index Is Still Up 110% YTD

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As we wrote on Sept. 23

Investing in the artificial intelligence (AI) sector should generate fantastic returns over the next decade but most people are not investing in it the best way. Why? Because they’re focused on the mega/large cap AI & related (AI&R) stocks that often trade for hundreds of dollars per share yet there are a number of less expensive, and potentially more explosive, micro/small cap AI&R stocks (i.e., stocks with market capitalizations above $50M but less than $2B) flying under the radar that warrant your attention.

Such stocks that trade for less than $10/share will get you wider exposure to that growth with less money invested. The top 10 performers in that sector are up 110% YTD - yes, 110%!

The munKNEE Micro/Small Cap AI Stocks Index

To assist you in determining which, if any, of the micro/small cap AI&R stocks have the greatest prospects of outperforming in the coming months and years we present below our new munKNEE Micro/Small Cap AI Stocks Index consisting of 10 micro/small cap AI&R stocks (average market capitalization of $311M) with

  • YTD price changes, ranked in descending order,
  • analyst 12-month price forecasts,
  • descriptions of their business,
  • current price-to-sales ratios (PSRs),
  • short interest percentages,
  • Altman Z-Scores,
  • Piotroski F-Scores, and
  • recent news in the media.
  1.  Applied Digital Corporation (APLD): up 178.8% YTD; 12-month forecast: up another 177%
    • APLD launched its AI Cloud services in May, 2023, that will provide high-performance computing power for AI applications, including large language model training, graphics rendering, and more, and has signed agreements with three (3) major customers in the last 4 months worth $640M including an agreement with Hewlett Packard in July to make its supercomputers accessible through Applied Digital's AI cloud service to support critical workloads such as AI. In August, APLD also achieved “Elite Partner” status in the NVIDIA Partner Network.
    • Market Capitalization: $545M
    • *Forward Price-to-Sales Ratio: 1.6 (excellent)
    • **Short Interest: 13.0 (high)
    • ***Altman Z-Score: 0.41 (high risk)
    • ****Piotroski Score: 4 (below average)
    • Read:
  2. Rekor Systems (REKR): up 147.5% YTD; 12-month forecast: up another 35%
  3. Innodata (INOD): up 130.3% YTD; 12-month forecast not available
    • provides AI data preparation services; collecting or creating training data; annotating training data; and training AI algorithms for its customers, as well as AI model deployment and integration services. In August it signed an agreement with its fourth Big Five technology customer to support their generative AI development initiatives.
    • Market Capitalization: $194M
    • Forward Price-to-Sales Ratio: 2.5
    • Short Interest: 12.7% (high)
    • Altman Z-Score: 4.5 (financially sound)
    • Piotroski Score: 3 (below average)
    • Read:
  4. Verses AI (VRSSF): up 121.7% YTD; 12-month forecast not available
  5. Digimarc (DMRC): up 109.4% YTD; 12-month forecast: down 11.5%
  6. BigBear.ai (BBAI): up 95.5% YTD; 12-month forecast: up another 129%
  7. Rigetti Computing (RGTI): up 91.8% YTD; 12-month forecast: up another 102%
  8. SoundHound AI (SOUN): up 79.8% YTD; 12-month forecast: up another 166%
  9. Evolv Technologies (EVLV): up 72.9% YTD; 12-month forecast: up another 99.5%
  10. GSI Technology (GSIT): up 34.1% YTD; 12-month forecast not available

The above 10 stocks have an average market capitalization of $311M, an average share price of $2.95 (when the outlier DMRC [$28.25/share], is excluded) and are up 108.6%, on average, YTD. Analysts forecast 7 of the above stocks (as noted) going up another 37.4%, on average, within the next 12 months.  

Conclusion

In deciding which, if any, of the above stocks you should invest in, given the above information, also ask yourself these 3 questions:

  1. Which companies have the potential of becoming major suppliers to any of the major AI developers?
  2. Which companies are developing or already have in place, AI products/applications that have the potential of becoming the next big thing?
  3. Which companies have AI technology, or technology in development, that makes them a prime acquisition target for one of the major AI tech companies?

If you find answers to any of the above questions, consider investing in one or more of the stocks covered in this article and you could be well-positioned to generate returns over the next decade.


Definitions:

  • *The P/S ratio (PSR) describes how much someone must pay to buy one share of a company relative to how much that share generates in revenue for the company. and, as such, determines whether its stock is cheap or overpriced in comparison to its peers. While the ideal ratio depends on the company and industry, 
    • the ratio is typically good when the value falls between one (1)  and two (2) and
    • a ratio of less than one (1) is even better.
  • According to Eqvista (see here), the average ratio for the semiconductor sector is 9.75 and, according to FullRatio (see here), it is 2.18 for information technology services stocks.
  • **A short interest as a percentage of float (source) shows the extent of investor sentiment:
    • below 10% indicates strong positive sentiment,
    • above 10% is pretty high indicating significant pessimistic sentiment, and
    • above 20% is extremely high indicating that:
      • a high number of shares have been sold short and/or that
      • a low number of shares are available to trade meaning that
      • investors have become more bearish and that if a sudden buying frenzy were to occur, short-sellers would have to frantically cover their positions.
  • ***The Altman Z-Score estimates a company's risk of bankruptcy: 
    • above 2.9 indicates the company is financially sound.
    • between 1.8 and 2.9 indicates a moderate risk of bankruptcy,
    • below 1.8 indicates the company is likely to go bankruptcy. 
  • ****The Piotroski F-Score is a score between zero and nine that reflects nine criteria used to determine the strength of a firm's financial position with nine being the best and zero being the worst.


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Disclosure: None

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