u/Few-Meringue-9965

▲ 8 r/soxl

What Comes Next in the Semiconductor Cycle? Who to Watch in the Next Phase

My core view was: this semiconductor rally is not over yet, but it is no longer in its early stage.

The first phase was led by core bellwethers like NVDA, AMD, and TSM, which drove index-level confirmation of the trend.

The second phase saw expansion into sub-sectors such as memory, AI optical communications, equipment, testing, and materials.

We are now clearly in the late stage of Phase Two.

If risk appetite in the market remains elevated, the third phase is likely to look like this: capital rotates further out from leading megacaps and mid-cap core names into smaller, higher-beta names with stronger narratives but less fully proven fundamentals.

This piece is about how I personally screen for stocks that are most likely to be driven by the market in this third phase of the semiconductor cycle.

Phase Three is not about randomly buying small caps. The focus should be on names with:

●  High beta (I am generally looking at market caps between $1B–$5B)

●  Close proximity to the AI thematic core

●  Increasing volume and liquidity

●  Early-stage relative strength

●  Clear catalysts (earnings beats, new orders, data center demand acceleration, product validation, pricing cycles, or institutional inflows)

Below are the key thematic areas most likely to attract attention in the next stage of the AI semiconductor boom:

 

Theme 1: Optical Interconnect / Silicon Photonics / Small-Cap Optical Communications

If memory has been one of the strongest fundamental drivers in this semiconductor cycle, then AI optical interconnect is one of the most narrative-driven high-beta themes.

The logic is straightforward:

As AI data centers scale rapidly, bandwidth bottlenecks between GPU clusters become increasingly severe. This drives demand for optical modules, optical components, silicon photonics, optical engines, and laser systems, all of which are likely to be repriced by the market.

Recent research from Citrini Research also highlights that AI compute demand is pulling optics out of the traditional telecom cycle, positioning optical interconnect as a core beneficiary of AI infrastructure buildouts.

Within this space, the large-cap and mid-cap leaders such as LITE and COHR have already seen significant rerating.

If we enter Phase Three, capital is likely to rotate further into smaller and more speculative optical names.Two small-cap names worth watching are POET and LASR:

● POET: More directly tied to silicon photonics and optical engine platforms. It carries a stronger narrative angle and is well positioned as a “high-conviction AI optical interconnect micro-cap story.”

● LASR: More exposure to laser systems and industrial lasers. The AI optical communication angle is less pure than POET, but it benefits from broader exposure to industrial manufacturing and AI infrastructure expansion, with a more established business base.

 

Theme 2: Power Semiconductors / AI Data Center Power Infrastructure

AI data centers are not just about GPUs and HBM. As the cycle matures, the market inevitably shifts attention toward power constraints: electricity supply, cooling systems, power conversion, SiC, GaN, and power management.

This theme is especially suited for Phase Three because it offers a simple, intuitive narrative:

The larger AI data centers become, the more extreme their power demand, and the more important power semiconductors become.

Two names to watch here are WOLF and NVTS:

● WOLF: A high-risk, high-beta SiC turnaround candidate. It has been heavily de-rated due to prior fundamental and cyclical pressures. However, if the market begins to price in AI data center power demand and a semiconductor cycle recovery, its upside convexity could be significant.

● NVTS: More focused on GaN power semiconductors and high-efficiency power architectures. It is closely aligned with AI server power upgrades and is easier for the market to understand thematically.

 

Theme 3: Secondary Expansion in Equipment, Testing, and Materials

If the semiconductor cycle continues to strengthen, equipment, testing, and materials will inevitably see renewed capital rotation.

The advantage of this theme is that the logic is structurally sound and industrially grounded.

The downside is that many of the leading names have already re-rated significantly.Therefore, in Phase Three, the focus is not on already fully priced winners, but on names that still have room for a second acceleration leg.

Key names to monitor include: AEHR, ICHR, UCTT, AXTI, and ATOM.

Ticker Rationale
AXTI Positioned across materials, optical communications, and compound semiconductors; narrative-friendly and easy for the market to reframe
AEHR High-beta test equipment name; tends to be aggressively bid when semiconductor equipment sentiment expands
ATOM Micro-cap with high volatility; fits classic Phase Three “sentiment-driven small-cap” profile
ICHR Beneficiary of equipment cycle recovery and order improvement, more cyclical and fundamentals-driven

 

Theme 4: B2B AI Commercialization + AI Robotics

In the third phase of the semiconductor rally, if capital continues searching for peripheral high-beta opportunities, an increasingly important theme is enterprise AI adoption and intelligent hardware applications.

Unlike traditional semiconductor plays, this theme focuses on real-world enterprise deployment scenarios and monetizable AI solutions, rather than pure chip or optical hardware narratives.

Markets tend to favor a combination of:

●  verifiable revenue growth

●  high narrative optionality

●  technological moat perception

This theme may only fully emerge later in the cycle, but it is worth watching.

Key names include:

● MAAS: B2B AI + distributed compute + AI robotics. Combines compute services, vertical industry models, and localized deployment, along with small lithium charging robotics hardware. It sits at the intersection of enterprise AI deployment and intelligent hardware.

● SOUN: Enterprise voice AI / agent systems. Reported Q1 2026 revenue growth of 52%, driven by automotive, IoT, enterprise, and consumer applications. It fits the “AI entering enterprise interaction layer” narrative.

● INOD: AI data engineering and training data services. Reported Q1 2026 revenue growth of 54%, with full-year guidance raised to 40%+. A clear beneficiary of enterprise AI model infrastructureization.

● SERV: AI delivery robotics. Focused on last-mile delivery robots. Commercialization is still early, but it offers strong narrative-driven upside potential.

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u/Few-Meringue-9965 — 13 days ago

Nasdaq daily call option volume reached 3.9 million contracts, second only to the 4.3 million recorded in November 2025, and more than four times the volume seen in 2021. Over the same period, the index posted 13 consecutive winning sessions — the longest streak since 2013 — with a cumulative gain of 17.7%, ranking among the best 13-day performances of the past two decades.

This is no ordinary rebound. It is a frenzy driven by the convergence of sentiment and liquidity. As both retail and institutional investors pile into leveraged bets on tech stocks, the market enters a self-reinforcing phase: the more it rises, the more they buy; the more they buy, the higher it goes.

But history serves as a reminder: the most feverish chasing of highs often occurs near trend reversals. When everyone believes "this time is different," risks are quietly building up.

u/Few-Meringue-9965 — 2 months ago

The U.S. stock market has recently staged a violent rebound, with the Nasdaq posting an 11-day winning streak to new highs. The previous three occurrences were: the early stage of the recovery from the 2009 financial crisis (panic short covering / aggressive re-entry), the melt-up at the end of the 2019 rate-cutting cycle, and the peak of the tech bull market in 2021.

The broader market has surged straight from 20,800 to above 24,000, leaving a massive vacuum zone between current prices and the short-term moving averages below. The underlying fuel for this rally has been mechanically triggered short squeezes from CTAs. As the trend broke out, CTAs were forced to enter, buying as much as $45 billion in a single week, while hedge funds are covering shorts at the fastest pace since March 2020. Once this several-hundred-billion pool of passive fuel is exhausted in the near term, a serious demand vacuum will emerge on the upside.

JPMorgan's Q2 collar defense signal remains evident, with the S&P 500 short call at 6,865.

Conclusion: Playing for lagging tech stocks (such as Microsoft) to catch up at these levels is extremely dangerous. When CTA buying dries up, the withdrawal of passive capital will leave no safe haven for any stock.

u/Few-Meringue-9965 — 2 months ago

The latest CTA positioning data shows that trend-following funds' exposure to U.S. stocks has dropped to historically low levels, significantly weakening liquidity support. Goldman Sachs estimates that while CTAs still have room to add positions in the near term, a break below the key pivot level of 6,725 on the S&P 500 would trigger a passive selling cascade, with projected outflows reaching $761 million within one month. Investors should closely monitor the market volatility risks arising from this liquidity tightening.

u/Few-Meringue-9965 — 2 months ago

A while back, someone shared a very interesting chart in the comments about long-term oil cycles. Before I had the chance to really digest the meaning behind it, the post was already deleted.

The core idea of that chart was similar — it showed the relative performance of precious metals, oil, and commodities versus stocks. Over the past 100 years, commodities have significantly outperformed stocks three times: the 1930s, the 1960s–70s, and the 2000s. These periods are closely tied to the Kondratieff cycles driven by technological revolutions.

  • The 1930s was the turning point of the Fourth Industrial Revolution (the transition from frenzy to mass deployment).
  • The 1960s–70s was the late stage of the Fourth Industrial Revolution and the dawn of the Information Revolution.
  • The 2000s was the transition from the frenzy phase of the Information Revolution to mass deployment.

Right now, the excess return of precious metals, oil, and commodities relative to stocks is still in its early stages. Does the current AI technology cycle resemble the 1930s and 2000s more, or the 1960s–70s?

  • If it is more like the former (1930s/2000s), then we may be facing a stock market frenzy followed by a crash.
  • If it is more like the 1960s–70s (Chart 2: stocks experienced a seven-year topping process), then today's large language models might resemble the significance of the transistor for the Information Revolution. Because the technology is still early, the speculative bull market will not center around the technology itself, but rather around high-quality large-cap stocks — similar to the Nifty Fifty. Those companies' valuations eventually became unsustainable, only to normalize over a long downtrend.

My personal view is that this time may be more like the 1960s–70s: the ultimate form of AI is likely to be built upon current model and hardware developments, and the better-performing stocks will be high-quality large caps (like the Nifty Fifty) rather than speculative small caps. If this framework holds, then the current valuations of large caps still have room to run before reaching Nifty Fifty levels. At the same time, the supercycle for gold and commodities may have only just begun.

u/Few-Meringue-9965 — 2 months ago
▲ 2 r/MAASstock+1 crossposts

China's already got nearly 44 million EVs, with close to 13 million new ones added last year alone. On paper, there are plenty of chargers. But anyone who's driven during a holiday knows the reality — highway rest areas are a total mess, lines everywhere. And good luck finding a charger in an old apartment complex or at a random outdoor event.

Then I came across this MAAS "Xiaoli" charging robot. The logic actually makes a lot of sense.

Specs: 150kWh LFP battery, 120kW fast charging. Can juice up a car in about 20 minutes. One robot can handle over a hundred cars a day. It moves autonomously... no driver needed. Perfect for places where building fixed chargers is a pain: highway rest stops, aging residential neighborhoods, temporary event sites, remote rural roads.

And as for the key thing, It's already in commercial deployment, not just a demo. 20 units went live earlier this year in some mountainous, humid regions in southern China, exactly the kind of challenging environment where you'd expect things to fail. And apparently, stability has been solid.

Compare that to fixed chargers, which need permitting, grid upgrades, and months of lead time. These robots just show up and work. And China's national policy, like a "three-year doubling" plan, explicitly calls for fixed + mobile charging to develop together, so government support is there.

Long term, they could also act as distributed energy storage: charge up cheap at night, sell back during peak hours, maybe even support V2G down the road.

In the world's largest EV market, this kind of flexible, on-demand charging actually feels like a more practical fix for range anxiety than just throwing more fixed piles at the problem.

What do you think about this?

Edited: Forget to mention that China is a major EV powerhouse, with a very high proportion of households owning EVs. The national stock of new enegry vehicles has exceeded 43 million units. Moreover, China has many public holidays and strong travel demand, and that makes it very common for EVs to run out of power during holidays, especially during the Chinese New Year, the coming May Day, and National Day, etc,.

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u/AdMajestic1252 — 2 months ago

This chart is quite intuitive: the gray areas represent periods of a weakening US dollar, and the purple line shows the relative performance between international developed markets (distinguishing them from emerging markets) and US stocks. The area above the zero line indicates periods when international markets are outperforming the US market. You can clearly see the relationship: during periods of a weak dollar, overseas stock markets tend to perform better than US stocks. However, the recent period is an exception — the dollar has weakened, but the purple line hasn't moved above zero.

Over the past few decades, the explanation for this phenomenon, aside from the direct impact of exchange rates on returns (when the dollar is weak, overseas returns denominated in US dollars automatically gain a currency translation benefit), also includes an economic development perspective: periods of a weak dollar have historically coincided with accelerating overseas growth. The US dollar exchange rate is driven by two core factors: one is the interest rate differential — whether US interest rates are higher or lower than overseas rates — and the other is the growth differential — which economy is growing faster. During periods of a weak dollar, both of these things typically happen simultaneously: the US is in a rate-cutting cycle, and at the same time, growth factors are spreading overseas.

What's curious is the recent performance. This chart uses a three-year rolling window. The past few months may just be the beginning of the cycle, and the international outperformance hasn't yet shown up. If that's the case, shifting focus from US stocks to overseas markets would be very meaningful. Another possibility is that this is a very unusual cycle — at least an exception to the patterns of the past 50 years: most of the global economy is stagnating, and so is the traditional part of the US economy, with only the US tech sector standing out as a bright spot in the stagnation. Which scenario do you think it is?

u/Few-Meringue-9965 — 2 months ago

ES daily chart / PLTR daily chart

Just a Chan Theory hobbyist sharing these charts. I'm not claiming to be right or wrong. Feedback and guidance from anyone who knows the theory is welcome. If you're here for something else, feel free to scroll past.

u/Few-Meringue-9965 — 2 months ago

This chart primarily illustrates the long-term trajectory of U.S. stocks (S&P 500) from 1967 to early 2026, driven by the dual forces of valuation levels and corporate profit margins.

Core Takeaways

1. Strong Correlation Between Profit Margins and the Index

  • Operating Margin (pink line): The operating margin of the MSCI USA Index is currently at an all-time high (approximately 15.0%). The chart clearly shows that every major rally in the S&P 500 has typically been accompanied by margin expansion.
  • Double Effect: From 2020 to the present, the market has experienced a sharp margin expansion from 9.9% to 15.0%, which has directly supported the S&P 500's slope trending significantly above its long-term regression line (yellow shaded band).

2. Valuation Levels at Historical Highs

  • P/E Ratio (green line): The current LTM P/E is approximately 23.2x. While below the 2000 dot-com bubble peak (29.0x) and the 2021 high (27.7x), it remains well above the historical median (approximately 15–16x).
  • P/S Ratio (blue line): This metric currently stands at approximately 3.17x, still at extremely high levels. This indicates that investors are willing to pay a higher premium for each dollar of sales, reflecting optimistic expectations for future growth or the increasing weight of technology stocks.

3. Trend and Deviation

  • Long-term Channel: The yellow shaded band represents the S&P 500's long-term logarithmic growth trend. The current index level (near 7,680) has clearly reached the upper edge of this channel, or even slightly broken above it, suggesting the market may be overheated or pricing in an overly perfect future outlook.
  • Macro Cycles (background colored vertical bands): Blue shaded areas typically correspond to undervalued/recessionary periods, while red shaded areas correspond to overvalued/overheated periods. The right side of the chart currently shows dense red areas, indicating significant valuation pressure at present.

Conclusion:

The current S&P 500 level is being driven higher by a combination of extremely strong corporate profitability (15% profit margins) and expanded valuation multiples (23x P/E) . While this "high profit + high valuation" combination is powerful, it also means the market has a low tolerance for any margin compression or valuation contraction (e.g., from persistently high interest rates).

u/Few-Meringue-9965 — 2 months ago