FNC-1: The Novacene Composite

Executive Signal Summary

I. What FNC-1 Is and Is Not

FNC-1 is a measurement instrument. It produces a weekly reading of where capital is being deployed across the four substrates of the AI transition, with constituents, weights, and calculation method published openly. Paired with the Belief Index overlay, it functions as a divergence detection tool, surfacing the gap between what capital is building and what prediction markets believe.

Three distinctions are worth making explicit, since FNC-1 could be confused with each.

Investment vehicles. The methodology is built for institutional readers tracking the AI transition: investors, board members, policymakers, analysts. Retail allocation is not the use case. There is no FNC-1 ETF and no plan to create one. The instrument exists to produce a weekly reading comparable across time rather than to generate returns.

AI ETFs. Existing AI-themed indices (the Roundhill Generative AI ETF, the Global X Robotics & AI ETF, the Bessemer AI Index) capture exposure to companies that benefit from AI. FNC-1 captures something structurally different: a substrate-weighted reading of where the transition is consuming capital. The selection criteria are about substrate position rather than thematic exposure. A company benefits from AI; a substrate constitutes the transition.

The SOX. The Philadelphia Semiconductor Index tracks pure compute exposure. FNC-1 weights compute at 30%; the remaining 70% sits in three other substrates that move on different cycles. Over the inaugural twelve-month window, FNC-1 returned 71.4% while the SOX returned 147.3%. The 76-point gap is the substrate diversification doing its work. If that gap closes to zero, the methodology has failed (see Falsification Triggers, Section VII).

II. The Four Substrates

The AI transition is a coordinated reallocation of capital across four interlocking substrates. Each substrate is a layer at which AI-transition capital is currently visible in public equity markets at meaningful scale.

Why these four and not five or three

These are the substrates where AI-transition capital deployment is visible in public equity markets at meaningful scale today. Adjacent substrates are reviewed annually for inclusion. The leading candidates for a fifth substrate are defense AI (Anduril is private; Palantir's defense exposure is partial; Lockheed AI is embedded inside a larger defense business) and robotics (still dominated by private actors and small-cap exposures). Climate-tech AI is too dispersed across categories to weight cleanly. Autonomous vehicles are a single-technology bet rather than a substrate.

What is deliberately excluded: the broad consumer technology stack (Apple, Amazon retail, Meta consumer revenue). Those companies benefit from AI as deployers. They sit downstream of the transition rather than constitute it.

III. Constituent Architecture (v0.1)

Version 0.1 of the FNC-1 is a seven-stock proxy basket. The proxy is the actual instrument used for the inaugural readings, sufficient on its own for repeatable methodology and substrate-level signal. Future versions will expand the basket toward fuller coverage of each substrate.

Each constituent is the cleanest publicly-traded representative of its substrate position, with sufficient market capitalization, liquidity, and disclosure to support repeatable methodology. The proxy is optimized for substrate representation rather than return.

Selection notes: Microsoft is assigned to Frontier rather than Compute despite substantial Azure infrastructure, because the Frontier exposure (OpenAI partnership) is what the index is designed to surface. Alphabet is assigned to Frontier rather than Compute despite TPU manufacturing, on the same logic: the Frontier signal is the one the methodology is built to capture. Constituents that span substrates are assigned to the substrate where their exposure is most differentiated.

Version 1.0 expansion: the production FNC-1 will likely expand to twenty-to-thirty names, with additional weight given to TSMC and Broadcom (Compute), Vistra and BWX Technologies (Energy), Meta and possibly select private-market proxies as they go public (Frontier), and several biological-intelligence names beyond Recursion. The expansion methodology will be specified in a future NCB.

IV. Weighting Scheme

The substrate weights reflect FP1's view of each substrate's structural importance to the AI transition, selected directly rather than derived from market capitalization.

Compute (30%). High enough to give compute its central role in scaling-law dynamics, but capped to prevent the index from becoming a SOX restatement. Compute is the substrate where most of the visible capital is currently moving; the cap is a deliberate constraint against single-substrate concentration.

Frontier (35%). The highest weight, because frontier labs sit between compute (their input) and applications (their output). They are the bottleneck through which transition value flows. The weight will be reviewed if the largest frontier labs go public and the substrate's market-cap exposure changes materially.

Energy (20%). Large enough to capture the binding constraint of the late 2020s, but smaller than compute and frontier because energy infrastructure operates on slower capital cycles. Capacity additions take years; the substrate's contribution to the transition signal lags.

Biological (15%). A present allocation that signals long-term substrate importance while reflecting the slower revenue ramp. The weight may increase to 20% if the substrate's revenue base expands materially in 2026-2027, with a corresponding reduction in Frontier.

Within each substrate, individual stocks are equal-weighted. This is a deliberate methodology choice: market-cap weighting within substrates would over-concentrate in the largest names (NVIDIA, Microsoft) and reduce the diversification that defines the basket's design. Equal-within-substrate weighting maintains the substrate-level signal as the primary axis.

The weights are reviewed annually under a stated process. Between reviews, they remain stable regardless of substrate performance.

V. Index Calculation

The FNC-1 Proxy Basket is calculated as follows:

1. At the start of the calculation window, each constituent's price is normalized to 1.0 (price divided by start-of-window price).
2. Each normalized series is multiplied by its target weight.
3. The weighted normalized series are summed across constituents to produce a single time series.
4. This series is multiplied by 100 to produce the index level.

The window is rebased to 100 at the start of each new annual measurement period (currently April 21 each year). Within a window, all readings are comparable to one another and to reference benchmarks rebased to the same start.

Rebalancing. The production methodology specifies quarterly rebalancing. On the first trading day of each quarter, the substrate weights and individual weights are re-applied to current constituent prices. Between rebalancing events, the basket drifts naturally with constituent prices.

Version 0.1 applies weekly rebalancing for simplicity in the chart-building pipeline. The production methodology will move to quarterly rebalancing in v1.0. The difference is small over a twelve-month window and does not materially change the substrate-level signal.

VI. Belief Index Overlay

The Belief Index complements the FNC-1. It reads what prediction-market participants currently believe about acceleration in the AI transition, normalized to a 0-100 scale where higher numbers mean stronger belief in continued acceleration.

The version 0.1 overlay draws from four Polymarket markets:

For each market, the "Yes" probability is the panel reading. Acceleration markets use the probability directly. Deceleration markets are inverted: panel reading equals one minus the probability. This keeps the index directionally consistent.

The Belief Index is the panel-weighted average of the four readings, multiplied by 100.

Why these four markets. Each addresses a distinct dimension of the transition. The AGI-by-2027 market reads capability ceiling. The GPT-6-by-2026 market reads capability cadence. The OpenAI-IPO-by-2026 market reads capital-market integration. The bubble-burst market reads deceleration risk. The selection is intentionally narrow. A panel of four markets allows movement in any one to be visible. Larger panels would smooth too much and reduce the overlay's value as a directional signal.

Why Polymarket only. Version 0.1 reads only Polymarket because it offers the largest active liquidity for AI-transition markets and a public API with no authentication required. This is a known limitation. A regulated-venue cross-check is on the near roadmap.

Future expansion. The panel will add Kalshi readings in a future version. Kalshi is regulated as a US Designated Contract Market, which provides a different demographic of participants than Polymarket and a regulatory cross-check on Polymarket's signal. Adding two Kalshi markets (a cross-venue AGI market and a longer-horizon AGI-by-2030 market) gives the panel six components and a regulated-venue null test against the Polymarket reading.

VII. Falsification Triggers

The methodology is invalidated, and the instrument suspended for re-specification, if any of the following occur. Each trigger is concrete and falsifiable.

When a falsification trigger fires, the instrument is suspended for re-specification. Re-specification is documented in a subsequent NCB.

VIII. Limitations

Four limitations of v0.1 are explicit:

Public-market visibility only. The FNC-1 captures publicly-traded substrate exposure. Privately-held frontier labs (Anthropic, OpenAI, xAI, Mistral) remain outside the Frontier substrate weighting until they go public. The OpenAI-IPO-by-2026 component of the Belief Index is partly a forecast of when this gap closes. Until it does, the Frontier substrate is read primarily through Microsoft's OpenAI partnership and Alphabet's owned-and-operated frontier work.

US-centric geography. Six of seven proxy constituents are US-listed. ASML is the exception. The index does not yet capture the substrate exposure of TSMC (Taiwan), Samsung Electronics (Korea), or non-US energy infrastructure providers. v1.0 will expand geographic coverage. Until then, the FNC-1 reads the AI transition primarily through US capital markets.

Substrate boundaries blur. Microsoft is a frontier-lab investor (OpenAI), a compute provider (Azure), and an enterprise software vendor. Alphabet is a frontier lab (Google DeepMind), a compute manufacturer (TPU), and an advertising business. The methodology assigns each constituent to a single substrate based on the exposure the index is designed to surface, but the assignments are judgment calls that will be revisited annually.

Belief Index is venue-concentrated. v0.1 reads only Polymarket. Until Kalshi is added, the Belief Index inherits the demographics, jurisdiction, and trading dynamics of a single venue. Polymarket is restricted from US persons, which means its participants skew toward international and institutional crypto-native traders. Calling the reading "what markets believe" would overstate the panel's representativeness; it reflects what one specific market believes, with that demographic skew baked in.

IX. Open Questions

Three questions for future versions:

Is biological intelligence weighted correctly? 15% reflects current market-cap presence of pure-play biological-intelligence names, but the substrate may be undervalued relative to its long-term importance. A weight increase to 20% would reduce Frontier's share to 30%. The decision will depend on how the substrate's revenue base develops in 2026-2027 and whether AlphaFold-derived drug discovery produces clinical readouts that change the public-market picture.

Should a fifth substrate be introduced? Defense AI is the leading candidate. If Defense exposure exceeds a meaningful public-market threshold by mid-2027 (defined provisionally as more than 5% of S&P 500 market cap attributable to AI-relevant defense activity), a fifth substrate may be warranted. Robotics is a secondary candidate; climate-tech AI is dispersed across categories that already have substrate representation.

How are retiring frontier labs handled? If a frontier lab is acquired, fails, or otherwise exits the public market between rebalancing events, the methodology has no current rule for substitution. v1.0 will specify a substitution rule, likely "next-largest pure-play in the same substrate, with substrate weight unchanged."

X. Roadmap

The methodology will evolve in three tiers.

Tier 1 (current). Seven-stock proxy basket, weekly rebalanced for chart-building. Belief Index from four Polymarket markets. Published weekly in State of the Transition. This is the version specified in the present paper.

Tier 2 (Q3 2026 target). Full constituent expansion to twenty-to-thirty names across the four substrates. Quarterly rebalancing logic. Substrate sub-indices (FNC-1 Compute, FNC-1 Energy, FNC-1 Frontier, FNC-1 Biological) for substrate-level reading. Backtested historical series for retroactive analysis. Kalshi belief markets added to the overlay.

Tier 3 (2027 target). Live hosted version on the FP1 Terminal page. Real-time chart with daily updates. API access for institutional readers. Substrate-level Belief Index breakdowns. Cross-venue belief cross-check fully operational.

Each tier will be documented in a subsequent NCB. The current paper specifies Tier 1 only.