The đŸ”„H.E.A.T.đŸ”„ Formula

AI Driven Insights to Spark Your Portfolio

January 29, 2025

The H.E.A.T. Formula is a radically different way to look at investing your portfolio.

‍H- Hedges, you should always have hedges and be agnostic as to being long or short. Bonds are not a hedge

‍E-Edges, you should always look for edges. Preferably these are edges with some sort of psychological underpinning, structural edges, or some sort of barrier to entry.

‍A-Asymmetric. Everything you do, be it trades or your overall portfolio, should be designed so that heads you win a lot, tails you lose a little.

‍T-Themes. You should always be invested in the top themes. Most everything else is just noise.

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1. Bullets From DeepSeek to Disruptors: Explore how one AI breakthrough (DeepSeek) reveals cost-effective strategies and under-the-radar opportunities beyond mainstream tech giants.

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3. Comparing & Contrasting Strategies: Discover how to harness AI to evaluate different investment approaches.

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Market Recap

Not a bad recovery yesterday. You worry on days like that about the sellers using the pop to unload, but the bulls were able to win out. Clear rotation out of Semis and AI infrastructure into the software names. Still think you need to be in all of those areas, but I wouldn’t chase the software names. What you’ve seen the past two days is the big institutions who got offsides have to flip there books. Wait for this to settle down if you don’t already have the software.

Looks like ASML had good earnings, which will be important.

“Anyone that lowers cost is good news for ASML,” Fouquet said at a press conference on Wednesday. “Lower cost means AI can be used in more applications, more applications mean more chips.”

One of ASML’s top customers, Taiwan Semiconductor Manufacturing Co., this month said it foresees spending $38 billion to $42 billion on technology and capacity in 2025, as much as 19% more than analysts expected.

Looks like they also think DeepSeek is a positive, which is also important.

Jefferies said it pretty well in a note this morning
..

Markets have stabilised after the Tech led sell-off on Monday. We remain of the view that the DeepSeek story is part of the evolution of the AI cycle and view it as a positive over the medium term. More companies and areas will have access to AI which will help in productivity. We still see it as a rotation story, with certain sectors (chipmakers and energy) likely to remain under pressure but rest of the sectors to shake off any Monday sell-off and move higher.

Thus, we continue to have a positive view on risky assets, but have a more cautious view on chipmakers and energy. Valuations are still stretched for certain Tech companies and the coming earnings season will need to justify the current high valuations.

And from JP Morgan


This development is not an end of US exceptionalism but more likely an accelerator. We have been of the view that the AI opportunity would eventually graduate from “Picks-and-Shovels” to “Apps-and-Services”. The lower cost of technology historically democratized opportunities for innovators and entrepreneurs with hardware eventually becoming a commodity compared to higher-margin Services with more sustainable growth (e.g., Software eclipsed Desktops and Chipmakers, Internet Service Providers surpassed Telecom Equipment and Services). Cheaper AI models should speed up and pull forward development of new products, services, and the expected gains in productivity, even if it comes at the expense of equipment providers in the short term. In summary, we see this development as a net positive for global equities as it should fuel incremental growth, earlier than expected AI-led efficiency gains, and could drive inflation lower over time.

Today is FOMC (should be a non-event but you never know) and we still have a ton of tech earnings to go (unlikely to be a non-event), but so far things are playing out very well for this whole DeepSeek thing to be a buying opportunity and not the end of the “AI Bubble”.

Software

I had DeepSeek analyze the stocks in the article (I’m running them in parallel), and make some suggestions for others. I’m in most of these but UiPath is a name that CPT has been bugging me to buy, just haven’t yet


Analysis of the Mentioned Stocks

  1. Microsoft (MSFT)

    1. Rating: 9/10Microsoft is a leader in AI with its Copilot offerings and Azure AI services. Its ability to integrate AI across its ecosystem (Office, Windows, Azure) gives it a significant edge. Lower AI compute costs could drive higher adoption of its AI tools, especially among enterprises.

    2. Key Risk: Competition from other cloud providers and potential margin compression if cost savings are passed to customers.

  2. Salesforce (CRM)

    1. Rating: 8/10Salesforce’s AI-driven CRM tools, like Einstein and Agentforce, position it well to benefit from AI cost reductions. The company’s focus on enterprise customers and its ability to monetize AI features (e.g., $2 per conversion) are strong positives.

    2. Key Risk: Slower-than-expected enterprise adoption of AI features and competition from niche AI-first CRM providers.

  3. Snowflake (SNOW)

    1. Rating: 8.5/10Snowflake’s data cloud platform is critical for AI development, as it enables efficient data storage and querying. The company’s ability to train large language models at low costs ($2 million for training compute) highlights its cost efficiency. Increased database queries due to AI proliferation could drive growth.

    2. Key Risk: Competition from other data platforms (e.g., Databricks) and potential pricing pressure.

  4. Adobe (ADBE)

    1. Rating: 7.5/10Adobe’s creative tools (e.g., Firefly AI) are well-positioned to benefit from lower AI training costs. The company’s ability to offer AI features on PCs and smartphones at lower costs could boost demand.

    2. Key Risk: Rising competition from AI-first creative tools and slower monetization of AI features.

  5. MongoDB (MDB)

    1. Rating: 8/10MongoDB’s NoSQL database is well-suited for AI applications, and reduced inferencing costs could drive higher adoption. The company stands to benefit from the proliferation of small language models and generative AI applications.

    2. Key Risk: Competition from traditional SQL databases and open-source alternatives.

  6. Okta (OKTA)

    1. Rating: 7/10Okta’s identity management solutions could see increased demand as AI agents proliferate and require secure access to applications. However, its growth is more tied to broader enterprise software trends than direct AI adoption.

    2. Key Risk: Slower-than-expected enterprise adoption of AI agents.

  7. ServiceNow (NOW)

    1. Rating: 7.5/10ServiceNow’s focus on AI-driven service desk tools and its exploration of consumption-based pricing could benefit from lower AI costs. However, the company’s speculative positioning in AI makes it a riskier play.

    2. Key Risk: Uncertainty around pricing models and competition from other workflow automation platforms.

Additional Names to Consider

The article missed some key players that could benefit from AI cost efficiencies and adoption. Here are a few:

  1. Datadog (DDOG)

    1. Rating: 8/10Datadog’s monitoring and analytics platform is critical for managing AI workloads. As AI adoption grows, demand for observability tools will increase.

    2. Key Risk: Competition from other monitoring platforms and pricing pressure.

  2. Palantir (PLTR)

    1. Rating: 8.5/10Palantir’s AI-driven data analytics platforms (e.g., AIP) are gaining traction in both government and commercial sectors. The company’s focus on AI and machine learning makes it a strong contender.

    2. Key Risk: High valuation and reliance on government contracts.

  3. CrowdStrike (CRWD)

    1. Rating: 8/10CrowdStrike’s AI-driven cybersecurity solutions are well-positioned to benefit from increased AI adoption, as more AI agents mean more attack surfaces to secure.

    2. Key Risk: Competition from other cybersecurity providers.

  4. UiPath (PATH)

    1. Rating: 7.5/10UiPath’s robotic process automation (RPA) tools are increasingly integrating AI capabilities. Lower AI costs could drive higher adoption of its automation solutions.

    2. Key Risk: Slower-than-expected enterprise adoption of RPA.

  5. Twilio (TWLO)

    1. Rating: 7/10Twilio’s communication APIs could benefit from AI-driven customer engagement tools. However, its growth is more tied to broader digital transformation trends.

    2. Key Risk: Competition from other communication platforms.

Conclusion

The software stocks mentioned in the article are well-positioned to benefit from AI cost efficiencies, with Microsoft, Snowflake, and Salesforce standing out as top picks. However, investors should also consider other names like Palantir, Datadog, and CrowdStrike, which have strong AI-driven growth potential. As always, diversification and careful consideration of valuation and competitive risks are key.

AI Power

I still believe in the AI power trade (ETF on this coming soon) but this is something that will be real important to watch
.

The rout shows how tendrils of the AI trade have spread beyond chip makers and big technology companies to sectors that usually have little to do with fast-growing tech stocks, such as oil-and-gas and utilities.

Interesting take from GPT


  • DeepSeek might reduce HPC intensity for advanced LLMs, but historically, efficiency leads to more total demand. Thus, the “AI power trade” might be dented in the short term, but not demolished.

  • Many energy and power stocks hammered by the initial meltdown could rebound once the market recognizes that cheaper HPC actually expands the universe of AI usage, driving more aggregate electricity demand.

  • Overall, the “AI power” trend remains 7/10, with a note that near-term HPC mania is under scrutiny, but broader AI adoption can sustain or even surpass previous demand expectations.

Winners in the bounce-back might include names that were heavily sold (CEG, VST, pipeline operators), while purely HPC-lumped land plays (like TPL) could face a more uncertain path.

SAP

Been one of my favorites for a while
..

GPT still likes it also


SAP’s robust enterprise footprint, strategic AI investments, and open stance on incorporating models like DeepSeek give it meaningful potential in the AI trade. While near-term HPC spending anxiety might weigh on the stock (the CFO noting “the bar is already very high”), SAP stands to benefit significantly as cheaper HPC unleashes broader AI usage in enterprise workflows. Hence, an 8/10 rating for SAP’s ability to harness the ongoing generative AI revolution—particularly once investors refocus on how these cost savings translate into easier adoption of SAP’s AI features and long-term revenue growth.

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