Sector Patterns in ATP Indicator Performance: Where the Edge Lives

Comparing ATP’s outperformance across materials, energy, biotech, and tech stocks to find which market types suit a pressure-based approach

The bars are color-coded by sector — green for materials & energy, blue for tech, coral for biotech, amber for financials — with the grey bars showing what buy & hold returned on the same stock over the same period. The gap between them is the edge.

Download Here: Absorption Trend Pressure (ATP) Indicator & Strategy : Beat Buy & Hold Across 40 Stocks

In a previous article, I published an indicator design article, which you can find at the link below:

[embed]Can a Pressure-Based Oscillator Beat Buy & Hold Across 40 Stocks? Most indicators tell you where price has been. ATP was built to detect where pressure is building — before the move…medium.com

In this article, we will continue our exploration by examining the sector patterns behind the edge we have identified.

How the 40 stocks were bucketed

The ATP stress test universe wasn’t built with sector analysis in mind. Stocks were selected across a wide range of industries, periods, and volatility profiles for robustness testing — not to overrepresent any one sector. For this analysis, the 40 tickers were grouped into 4 broad categories based on business type:

Materials & Energy covers commodity producers, refiners, and industrial manufacturers — businesses whose revenues are directly tied to physical commodity cycles. CENX (aluminum), PTEN (oil & gas drilling), HOV (homebuilding), OI (glass), GPRE (ethanol), NGL, NRP, AES, PRM, KRO.

Tech & Electronics covers semiconductors, photonics, connectivity hardware, and electronics — high-beta, cycle-sensitive businesses where price momentum tends to be violent in both directions. AXTI, VICR, VIAV, AAOI, CIEN, MARA, ACLS, KOPN, MVST, VECO, MCHB, SNPS.

Biotech & Healthcare covers clinical-stage and small-cap healthcare companies — binary-event driven, often with no revenue and extreme price swings around data readouts. KOD, STAA, ACRS, ADPT, KURA, SYRE, DNTH, TNGX, IMNM, OWLT, AGL.

Financial & Services covers banks, asset managers, and services businesses — typically lower-volatility, mean-reverting, with structurally different price behavior from the other 3 groups. CSV, CRD-B, SFST, WT, BBW, NEWT, STGW.

Materials & Energy: ATP’s strongest home ground

This is where ATP’s pressure-based logic shines hardest. The median outperformance across the materials and energy bucket is extraordinary — driven by CENX (+7,614%), HOV (+2,401%), PTEN (+2,877%), and OI (+2,188%) as standout performers.

The structural reason makes intuitive sense. Commodity-linked stocks are volatility machines. They trend violently, mean-revert sharply, and spend long periods under accumulation or distribution before explosive directional expansion. That’s precisely the environment where wick-based absorption signals are most reliable — large lower wicks during downtrends mark where industrial buyers absorb forced selling, and the ATP composite catches the shift before price confirms it.

Cyclicality amplifies the edge further. Oil, aluminum, and construction materials move in multi-year commodity supercycles. A pressure-based system that catches the turn early and holds through the expansion captures the full magnitude of those moves — buy & hold, by contrast, catches the full cycle including the crash.

The one exception worth noting is PRM (Perimeter Solutions), which only barely outperformed buy & hold at +1.05 percentage points. It was a short-period test (2025–2026) with minimal data. Short windows penalize trend-following systems; there’s simply not enough time to express the edge.

Tech & Electronics: volatile, rewarding, but uneven

Tech is ATP’s second-strongest sector, but the distribution is wider and the individual results more variable.

The top performers — AXTI (+8,319%), VIAV (+1,797%), AAOI (+2,529%), VICR (+2,520%) — are all mid-cap hardware and photonics companies with extreme cyclicality. They behave more like commodity stocks than software companies: boom/bust revenue cycles, institutional accumulation phases, violent corrections. ATP treats them similarly.

The weaker performers — MCHB (+66%), KOPN (+258%), VECO (+134%) — tend to be lower-liquidity names or those in secular decline. MCHB’s near-zero outperformance is notable; its price history is characterized more by slow structural erosion than trend-driven cycles, which suits buy & hold poorly and ATP barely better.

MARA (crypto infrastructure) is worth isolating. ATP returned +1,178% against buy & hold’s -48% — a gap of +1,226 percentage points. MARA’s price history is driven by Bitcoin cycle narrative, not fundamental cash flows, which creates exactly the kind of momentum-absorption dynamic ATP was designed for. When absorption signals fire in MARA, it’s because large hands are accumulating crypto-adjacent exposure. When the selling pressure reverses, it reverses hard.

Biotech & Healthcare: smaller edges, but real ones

This is where the analysis gets most interesting — and most honest.

Biotech is the sector where ATP’s edge is weakest. Median outperformance is positive across the bucket, but the individual results show why: most biotech outperformance comes from ATP successfully avoiding the downside of clinical failures, not from catching the upside of approvals.

SYRE (Spyre Therapeutics) is instructive. Strategy return: +58%. Buy & hold: -59%. That’s +117 percentage points of outperformance — but ATP generated it by getting out of the way, not by catching a trend. The stock had violent selloffs followed by partial recoveries; ATP’s threshold-based exit logic stepped aside during the worst of it.

KOD (Kodiak Sciences) shows the same dynamic. Buy & hold: -56%. ATP strategy: +1,077%. A clinical-stage company where passive holding was a disaster. ATP’s exits avoided the worst drawdowns and reinvested in the rebounds.

The weaker biotech results — IMNM (+54%), DNTH (+89%) — tend to be very recent tests (2022–2026) with few trades. IMNM generated only 2 trades total in its test window. That’s a structural limitation of trend-following in short windows: you need enough price cycles to express the edge.

The broader lesson for biotech: ATP does not predict binary events. It can’t tell you whether a trial will succeed. What it can do is get out of a deteriorating technical trend before the confirmed bad news, and re-enter after absorption signals indicate the selling is exhausted. That’s a meaningful edge — just a smaller and less reliable one than in cyclical sectors.

Each dot is one stock. The horizontal axis is ATP’s win rate on that ticker; the vertical axis is the max drawdown sustained during the strategy’s run. A few patterns emerge immediately: biotech and financial stocks cluster toward the lower-right — relatively higher win rates, but also lower drawdowns (smaller moves, less trend persistence). Materials and tech stocks sprawl across the upper half — bigger drawdowns, but also much bigger outperformance to compensate.

A few stocks exhibit a 100% win rate; however, this is likely the result of an insufficient sample size. With so few trades, the statistic is not yet reliable, so it should not be overemphasized.

Financial & Services: the most honest underperformance story

Financials deserve a frank assessment. ATP beats buy & hold across all seven stocks in this bucket, but the margins are the slimmest of any sector.

CSV (+394% vs +802% buy & hold) is the most instructive case. Buy & hold returned 802% over 26 years — a solidly performing business that compounded quietly. ATP returned 1,196%, beating it by +394 percentage points. That sounds good until you note that buy & hold captured most of the value here without the complexity of a systematic strategy. The pressure-based edge exists, but it’s competing against a strong passive baseline.

CRD-B shows a similar pattern — 1,679% strategy vs 1,240% buy & hold, a +439 point edge over 42 years. SFST added +232 points. These are real edges, but they’re earned across decades in lower-volatility, lower-cycle-amplitude stocks.

The structural reason is this: financials and services companies don’t have commodity supercycles. Their price behavior is shaped by interest rates, credit conditions, and earnings revisions — forces that tend to create smoother, shallower trends rather than violent absorption-and-expansion cycles. ATP’s absorption ratio fires on dramatic wick behavior; in a stock that moves 1–2% a day, there’s less dramatic wick behavior to detect.

WT (WisdomTree) is the outlier — +1,040% over buy & hold — but notably it’s an asset manager with exposure to crypto and alternative assets. Its price behavior is more volatile and cycle-driven than a traditional bank, which explains why ATP finds more edge there.

What this means for instrument selection

The sector analysis converges on a clear principle: ATP’s edge scales with volatility amplitude and trend persistence.

The best candidates share three characteristics. First, they operate in markets where prices move in multi-year cycles rather than around a mean — commodity producers, semiconductors, high-beta hardware. Second, their institutional ownership creates large, detectable absorption events — when a hedge fund is accumulating CENX ahead of an aluminum cycle, it shows up in wick asymmetry over weeks. Third, they have enough trading history for the walk-forward optimization to adapt parameters across multiple market regimes.

The weakest candidates tend to be stable-compounders (low-beta businesses that drift upward), clinical-stage biotechs with binary event risk (where a single FDA announcement moves the stock 40% overnight, bypassing technical structure entirely), and recent IPOs or very short data windows where WFO has insufficient history to stabilize parameters.

This isn’t a criticism of ATP’s design — it’s a description of when any trend-following, absorption-based system can be expected to outperform. The edge lives in volatile, cycle-driven, institutionally-active markets. The more a stock behaves like a commodity, the better ATP tends to work on it.

If you’re using the ATP framework for stock trading, the sector results suggest a ranking of effort: start with materials, energy, and high-beta tech hardware. Expect meaningful edge. Apply it to financial services and stable-growth names as a secondary screen — the edge exists but is thinner and requires more patience. Treat clinical-stage biotech as a special case where ATP can help with loss avoidance more than gain capture.

None of this tells you which stocks to trade tomorrow. What it tells you is where the pressure-based logic is structurally best suited — and that’s worth knowing before you run a backtest.

The full ATP Python framework — including the walk-forward optimization engine, 40-stock stress test scaffolding — is available now. Download the complete codebase on Gumroad.

Download Here: Absorption Trend Pressure (ATP) Indicator & Strategy : Beat Buy & Hold Across 40 Stocks

This article is not investment advice but is created solely for educational purposes. Investing involves risks and volatility, and users of any trading system should carefully conduct their own research before proceeding.

Follow Me on Medium: Kryptera

Follow Me on Gumroad: Kryptera Gumroad

Follow Me on Substack: Kryptera Substack