Methodology
Last updated:
INTRINSIC ENGINE™
Digital-asset valuation has lacked a defensible standard. Sentiment-driven prices, opaque proprietary models, and speculative forecasts have left domain experts without a consistent answer to a simple question: what is this asset actually worth?
AIREPORT's Intrinsic Engine™ produces Structural Value (SV) — a deterministic, bidirectional fair-value assessment with a documented empirical record across more than 1,200 measured market moments and nearly two years of history. Inputs are traceable to their source; outputs are reproducible on demand.
Methodological Highlights
Aggregated market data. Foundation data drawn from CoinMarketCap, which aggregates price, volume, market capitalization, and circulating supply across hundreds of digital-asset exchanges globally.
Appraisal, not prediction. Structural Value provides a fair-value assessment based on each asset's market behavior. It is not a forecast or trading signal.
Bidirectional by design. Universal methodology assesses both overvaluation and undervaluation with a single deterministic formula — no per-asset tuning or custom parameters.
On-chain supply is built in. Circulating-supply changes and supply-normalized comparisons are part of every analysis — ensuring valuation comparisons across assets with structurally different supply profiles remain meaningful.
Documented empirical record. Across a defined cohort of 15 digital assets and nearly two years of history, 87.4% of assessments are confirmed by subsequent market behavior within 30 days and 91.0% within 90 days. Full breakdown in Validation.
Reproducible and timestamped. Every calculation is deterministic and saved as a permanent record — suitable for the standard of scrutiny professional work requires.
Who This Serves
AIREPORT is built for professionals who need a defensible, objective valuation of digital assets — not a trading signal, not a speculative forecast, and not a range that requires further interpretation.
Family law attorneys use Structural Value (SV) as an impartial, mathematically derived figure for equitable distribution of digital asset holdings. One number per asset, backed by a consistent and durable methodology resistant to bias claims. The same methodology that produced last month's valuation produces next week's reassessment — because the process is the same, the results are comparable and defensible.
Financial advisors and wealth managers use Structural Value to bring the same analytical rigor to digital asset holdings that they apply to every other asset class. When a client holds digital assets, Structural Value provides a firm number for rebalancing, reporting, and recordkeeping.
What Structural Value Measures
Structural Value assesses an asset's fair value through measures of internal coherence and consistent market behavior. Each value assessment is a statement of what the asset structurally merits at that time.
The mental model is appraisal, not prediction. A property appraiser reports value based on comparable sales and condition factors, not future sale prices. Structural Value reports the fair value of digital assets using historical consistency patterns and integrity metrics.
Market prices routinely deviate from equilibrium. Sentiment, liquidity events, and speculation push price away from fair value — sometimes for days, other times for months. Structural Value represents the gravitational center toward which price tends to return; this is a metaphor for the observable pattern, not a claim about market mechanics. The underlying mechanism is the structural-evidence calibration described in How the Engine Works.
For professionals, Structural Value is a fair-value reference point, not a price prediction — validated by whether the market reaches the assessed value within defined forward windows. The standard horizons are 30 and 90 days; results for both are published under Validation.
Bidirectional Assessment
The methodology assesses overvaluation and undervaluation through a single deterministic mechanism. When SV sits below market price, the engine assesses overvaluation; when SV sits above market price, undervaluation. Both directions are structurally meaningful; neither is a speculative call.
The same formula runs for every asset in the cohort, with no manual parameters, per-asset tuning, or human input. The magnitude of the assessment in each direction scales with the strength of the evidence: weak signals produce small adjustments, strong signals produce larger ones.
For attorneys, this means the methodology cannot be challenged as directionally biased — it applies the same analysis regardless of whether the result favors or disfavors either party. For advisors, the methodology offers a consistent way to assess a digital asset allocation rather than using asset-specific models.
This holds for stablecoins as well. Because a peg-tracking asset shows little structural divergence between current price and its own historical price behavior, SV converges toward market price by the same mechanism that governs every other asset — the same formula that produces a 12% undervaluation signal for an altcoin produces a near-zero signal for USDC. The SV calculation applies identically to stablecoins and volatile assets; depeg episodes surface through a dedicated regime-change detector calibrated to peg-tracking behavior.
How the Engine Works
The Intrinsic Engine™ evaluates each asset against its own history across six distinct time horizons, each derived from a mathematically structured reflection period spanning from approximately three weeks to two years. Rather than relying on a single lookback window, the system examines how consistently an asset's current price relates to its own structural history across multiple timeframes simultaneously. The empirical record behind the current production engine draws on more than 8,000 snapshot points, each producing a full factor-and-horizon matrix of derived measures.
The engine combines three independent inputs:
Structural integrity. A quality measure of the data environment — how stable, consistent, and well-behaved the asset's relationship to its own history is within and among each horizon.
Non-linear consistency. A measure of how consistently price relates to reflection across the six horizons. The non-linear transform dampens noisy or inconsistent signals more than proportionally, preventing weak evidence from producing strong assessments.
Regime-aware calibration. Per-asset confidence is calibrated against real-time market conditions. When recent volatility is contracting, the engine expresses its assessments more conservatively; when conditions are stable or expanding, full confidence is maintained.
The result is a single synthesized fair-value number — not a range — reflecting the strongest available structural evidence, tempered by current market conditions through the regime-aware calibration described above.
The current Intrinsic Engine generation (v14) powers the production analytics. Each generation tightened what came before — eliminating factors, special cases, and tuning parameters that testing showed were carrying noise rather than signal.
Data Sources
Market data — price, OHLCV (daily open/high/low/close/volume), market capitalization, and circulating supply — is sourced from CoinMarketCap's aggregated exchange feeds. Aggregation matters: rather than relying on any single exchange's prices (each carrying its own liquidity profile, regional concentration, and reporting cadence), the data reflects activity across the venues where the asset actually trades.
Circulating supply is treated as a first-class input. On-chain supply dynamics — issuance, burns, lockups, and net distribution changes — are reflected in the data the engine consumes, ensuring that valuation comparisons across assets with structurally different supply profiles remain meaningful. Market capitalization is the product of price and supply; an honest assessment requires both inputs to be current and verifiable.
All ingested data is traceable to its origin and timestamped at the moment of ingestion. The data the engine sees today is the data the audit trail preserves for tomorrow.
Asset Integrity Score
The Asset Integrity Score (AIS) is a separate system that rates an asset's data health on a scale of 0–100%.
AIS is built from several analytical factors. These include market position, supply behavior, model agreement, intrinsic consistency, price stability, and elasticity. All are measured across the same six composite time horizons, giving a complete view of each asset's analytical strength at any time.
AIS and SV are complementary but independent. SV is the engine's fair-value assessment — the substantiated number a professional reports, with the engine's non-linear and regime-aware calibration already applied. AIS is a separate measurement of the asset itself: how structurally coherent its data behavior is across time. A professional does not use AIS to interpret SV; that calibration is already applied within the SV calculation itself. AIS answers a different question entirely: not what is this asset worth? buthow structurally coherent is this asset compared to others in the portfolio?
For a multi-asset portfolio manager, AIS is the asset-characterization signal — it surfaces which holdings behave with consistent structural patterns and which carry noisier underlying data. The fair-value assessment for each holding stands on its own.
Structural Change Detection
AIREPORT monitors portfolio assets for structural changes using automated anomaly detection. It tracks 11 types of analytical events across 7 categories: valuation extremes, integrity deterioration, model regime shifts, supply disruptions, equilibrium bias changes, stablecoin regime changes, and systemic cross-asset patterns.
Detection thresholds adapt per asset against its historical baseline, not fixed values. This prevents false positives for volatile assets while remaining sensitive to stable ones. A second-stage detector adds market-stress awareness: acute anomaly thresholds tighten when the composite stress signal — a synthesis of cohort-wide volatility, model-divergence, and equilibrium-bias indicators — is elevated.
For wealth managers, this is the structural-change monitor. Shifts in the asset's profile appear as plain-language alerts with explanations as soon as data supports them.
VALIDATION
How market confirmation is measured
The validation standard measures whether the market actually reaches the assessed value. For a bearish assessment (SV below market), a touch occurs if the market's daily low reaches SV on any day within the forward window. For a bullish assessment (SV above market), a touch occurs if the market's daily high reaches SV on any day within the forward window.
This standard uses intraday high/low prices by design rather than closing prices. A closing-price standard would credit the assessment only when the day ended at the assessed level; an intraday standard credits any moment the market transacted at that level, including brief wicks. The methodology chooses the intraday standard because it tests whether the assessed value is one the market actually engaged with at any point in the window, rather than only at the daily close.
Headline result
The current production engine has been tested against 1,217 real market moments over nearly two years. 87.4% of assessments are confirmed within 30 days; 91.0% within 90 days. Bearish assessments confirm at 92.1% / 96.1% (30d / 90d); bullish assessments confirm at 84.5% / 87.4%. The result is reproducible from backtest data on demand and updates as market history accumulates — a living standard, not a single measurement.
Per-asset consistency
Per-asset 30-day confirmation ranges from approximately 75% to over 90% across the cohort. The spread reflects each asset's own structural characteristics; no asset has driven the aggregate result disproportionately, and the methodology has not been tuned to favor any individual asset. Confirmation rates are consistent when measured at daily, weekly, monthly, and quarterly forward windows, indicating the result is not a narrow-window phenomenon.
When assessments are not confirmed
Approximately 12.6% of assessments are not confirmed by the market within the 30-day measurement window — 7.9% bearish and 15.5% bullish. The bullish leg degrades faster historically; the methodology applies asymmetric scaling by design to bound that degradation. An unconfirmed assessment is not a wrong assessment; it is often one where the market was approaching the level but hadn't reached it within the window. For the worst 1% of misses, the deviation between the assessed value and the closest price the market actually reached is approximately 7% for bearish assessments and approximately 10% for bullish. The maximum observed deviation across the entire record is 8.0% bearish, 13.4% bullish.
Cohort and generalization
The empirical record derives from a defined cohort of 15 digital assets — 13 non-stablecoin and 2 stablecoin — comprising diverse market roles: established, large-capitalization assets; mid-capitalization and infrastructure assets; and gold-backed and fiat-backed value reference assets. The cohort was tested over an approximately two-year historical window spanning both expansion and contraction regimes. The same deterministic methodology applies to assets outside the cohort; per-asset empirical records accumulate as market history lengthens. For professionals presenting assessments in contested contexts, the methodology applies universally and the backtest record speaks directly to the cohort on which it was measured.
How to Read the Number
Wider gaps carry less conviction. The engine's bounded design dampens the assessment as the gap between SV and market price widens. Large SV–market gaps signal weaker structural conviction, not stronger — a bounded-output property of the methodology.
Market validation through price action. The intraday touches described under Validation are strong confirmations of the fair-value assessment — they show the assessed level is one the market is actively engaged with, not a theoretical estimate.
Built for professional timeframes. Structural Value is designed for professionals who assess value over weeks, months, and quarters — estate valuations, fund reporting, fiduciary due diligence, equitable distribution, and settlement analysis. It is not a trading signal.
Deterministic and auditable. The number is built to withstand professional scrutiny: a documented methodology, a complete audit trail, and a reproducible calculation path from input to output.
What You Receive
AIREPORT generates professional reports showing portfolio-level and per-asset structural valuations alongside integrity scores and risk events. Whether the report supports a settlement negotiation, a quarterly client review, or a fiduciary filing, the methodology is consistent and the audit trail is complete.
Methodology
Last updated:
INTRINSIC ENGINE™
Digital-asset valuation has lacked a defensible standard. Sentiment-driven prices, opaque proprietary models, and speculative forecasts have left domain experts without a consistent answer to a simple question: what is this asset actually worth?
AIREPORT's Intrinsic Engine™ produces Structural Value (SV) — a deterministic, bidirectional fair-value assessment with a documented empirical record across more than 1,200 measured market moments and nearly two years of history. Inputs are traceable to their source; outputs are reproducible on demand.
Methodological Highlights
Aggregated market data. Foundation data drawn from CoinMarketCap, which aggregates price, volume, market capitalization, and circulating supply across hundreds of digital-asset exchanges globally.
Appraisal, not prediction. Structural Value provides a fair-value assessment based on each asset's market behavior. It is not a forecast or trading signal.
Bidirectional by design. Universal methodology assesses both overvaluation and undervaluation with a single deterministic formula — no per-asset tuning or custom parameters.
On-chain supply is built in. Circulating-supply changes and supply-normalized comparisons are part of every analysis — ensuring valuation comparisons across assets with structurally different supply profiles remain meaningful.
Documented empirical record. Across a defined cohort of 15 digital assets and nearly two years of history, 87.4% of assessments are confirmed by subsequent market behavior within 30 days and 91.0% within 90 days. Full breakdown in Validation.
Reproducible and timestamped. Every calculation is deterministic and saved as a permanent record — suitable for the standard of scrutiny professional work requires.
Who This Serves
AIREPORT is built for professionals who need a defensible, objective valuation of digital assets — not a trading signal, not a speculative forecast, and not a range that requires further interpretation.
Family law attorneys use Structural Value (SV) as an impartial, mathematically derived figure for equitable distribution of digital asset holdings. One number per asset, backed by a consistent and durable methodology resistant to bias claims. The same methodology that produced last month's valuation produces next week's reassessment — because the process is the same, the results are comparable and defensible.
Financial advisors and wealth managers use Structural Value to bring the same analytical rigor to digital asset holdings that they apply to every other asset class. When a client holds digital assets, Structural Value provides a firm number for rebalancing, reporting, and recordkeeping.
What Structural Value Measures
Structural Value assesses an asset's fair value through measures of internal coherence and consistent market behavior. Each value assessment is a statement of what the asset structurally merits at that time.
The mental model is appraisal, not prediction. A property appraiser reports value based on comparable sales and condition factors, not future sale prices. Structural Value reports the fair value of digital assets using historical consistency patterns and integrity metrics.
Market prices routinely deviate from equilibrium. Sentiment, liquidity events, and speculation push price away from fair value — sometimes for days, other times for months. Structural Value represents the gravitational center toward which price tends to return; this is a metaphor for the observable pattern, not a claim about market mechanics. The underlying mechanism is the structural-evidence calibration described in How the Engine Works.
For professionals, Structural Value is a fair-value reference point, not a price prediction — validated by whether the market reaches the assessed value within defined forward windows. The standard horizons are 30 and 90 days; results for both are published under Validation.
Bidirectional Assessment
The methodology assesses overvaluation and undervaluation through a single deterministic mechanism. When SV sits below market price, the engine assesses overvaluation; when SV sits above market price, undervaluation. Both directions are structurally meaningful; neither is a speculative call.
The same formula runs for every asset in the cohort, with no manual parameters, per-asset tuning, or human input. The magnitude of the assessment in each direction scales with the strength of the evidence: weak signals produce small adjustments, strong signals produce larger ones.
For attorneys, this means the methodology cannot be challenged as directionally biased — it applies the same analysis regardless of whether the result favors or disfavors either party. For advisors, the methodology offers a consistent way to assess a digital asset allocation rather than using asset-specific models.
This holds for stablecoins as well. Because a peg-tracking asset shows little structural divergence between current price and its own historical price behavior, SV converges toward market price by the same mechanism that governs every other asset — the same formula that produces a 12% undervaluation signal for an altcoin produces a near-zero signal for USDC. The SV calculation applies identically to stablecoins and volatile assets; depeg episodes surface through a dedicated regime-change detector calibrated to peg-tracking behavior.
How the Engine Works
The Intrinsic Engine™ evaluates each asset against its own history across six distinct time horizons, each derived from a mathematically structured reflection period spanning from approximately three weeks to two years. Rather than relying on a single lookback window, the system examines how consistently an asset's current price relates to its own structural history across multiple timeframes simultaneously. The empirical record behind the current production engine draws on more than 8,000 snapshot points, each producing a full factor-and-horizon matrix of derived measures.
The engine combines three independent inputs:
Structural integrity. A quality measure of the data environment — how stable, consistent, and well-behaved the asset's relationship to its own history is within and among each horizon.
Non-linear consistency. A measure of how consistently price relates to reflection across the six horizons. The non-linear transform dampens noisy or inconsistent signals more than proportionally, preventing weak evidence from producing strong assessments.
Regime-aware calibration. Per-asset confidence is calibrated against real-time market conditions. When recent volatility is contracting, the engine expresses its assessments more conservatively; when conditions are stable or expanding, full confidence is maintained.
The result is a single synthesized fair-value number — not a range — reflecting the strongest available structural evidence, tempered by current market conditions through the regime-aware calibration described above.
The current Intrinsic Engine generation (v14) powers the production analytics. Each generation tightened what came before — eliminating factors, special cases, and tuning parameters that testing showed were carrying noise rather than signal.
Data Sources
Market data — price, OHLCV (daily open/high/low/close/volume), market capitalization, and circulating supply — is sourced from CoinMarketCap's aggregated exchange feeds. Aggregation matters: rather than relying on any single exchange's prices (each carrying its own liquidity profile, regional concentration, and reporting cadence), the data reflects activity across the venues where the asset actually trades.
Circulating supply is treated as a first-class input. On-chain supply dynamics — issuance, burns, lockups, and net distribution changes — are reflected in the data the engine consumes, ensuring that valuation comparisons across assets with structurally different supply profiles remain meaningful. Market capitalization is the product of price and supply; an honest assessment requires both inputs to be current and verifiable.
All ingested data is traceable to its origin and timestamped at the moment of ingestion. The data the engine sees today is the data the audit trail preserves for tomorrow.
Asset Integrity Score
The Asset Integrity Score (AIS) is a separate system that rates an asset's data health on a scale of 0–100%.
AIS is built from several analytical factors. These include market position, supply behavior, model agreement, intrinsic consistency, price stability, and elasticity. All are measured across the same six composite time horizons, giving a complete view of each asset's analytical strength at any time.
AIS and SV are complementary but independent. SV is the engine's fair-value assessment — the substantiated number a professional reports, with the engine's non-linear and regime-aware calibration already applied. AIS is a separate measurement of the asset itself: how structurally coherent its data behavior is across time. A professional does not use AIS to interpret SV; that calibration is already applied within the SV calculation itself. AIS answers a different question entirely: not what is this asset worth? buthow structurally coherent is this asset compared to others in the portfolio?
For a multi-asset portfolio manager, AIS is the asset-characterization signal — it surfaces which holdings behave with consistent structural patterns and which carry noisier underlying data. The fair-value assessment for each holding stands on its own.
Structural Change Detection
AIREPORT monitors portfolio assets for structural changes using automated anomaly detection. It tracks 11 types of analytical events across 7 categories: valuation extremes, integrity deterioration, model regime shifts, supply disruptions, equilibrium bias changes, stablecoin regime changes, and systemic cross-asset patterns.
Detection thresholds adapt per asset against its historical baseline, not fixed values. This prevents false positives for volatile assets while remaining sensitive to stable ones. A second-stage detector adds market-stress awareness: acute anomaly thresholds tighten when the composite stress signal — a synthesis of cohort-wide volatility, model-divergence, and equilibrium-bias indicators — is elevated.
For wealth managers, this is the structural-change monitor. Shifts in the asset's profile appear as plain-language alerts with explanations as soon as data supports them.
VALIDATION
How market confirmation is measured
The validation standard measures whether the market actually reaches the assessed value. For a bearish assessment (SV below market), a touch occurs if the market's daily low reaches SV on any day within the forward window. For a bullish assessment (SV above market), a touch occurs if the market's daily high reaches SV on any day within the forward window.
This standard uses intraday high/low prices by design rather than closing prices. A closing-price standard would credit the assessment only when the day ended at the assessed level; an intraday standard credits any moment the market transacted at that level, including brief wicks. The methodology chooses the intraday standard because it tests whether the assessed value is one the market actually engaged with at any point in the window, rather than only at the daily close.
Headline result
The current production engine has been tested against 1,217 real market moments over nearly two years. 87.4% of assessments are confirmed within 30 days; 91.0% within 90 days. Bearish assessments confirm at 92.1% / 96.1% (30d / 90d); bullish assessments confirm at 84.5% / 87.4%. The result is reproducible from backtest data on demand and updates as market history accumulates — a living standard, not a single measurement.
Per-asset consistency
Per-asset 30-day confirmation ranges from approximately 75% to over 90% across the cohort. The spread reflects each asset's own structural characteristics; no asset has driven the aggregate result disproportionately, and the methodology has not been tuned to favor any individual asset. Confirmation rates are consistent when measured at daily, weekly, monthly, and quarterly forward windows, indicating the result is not a narrow-window phenomenon.
When assessments are not confirmed
Approximately 12.6% of assessments are not confirmed by the market within the 30-day measurement window — 7.9% bearish and 15.5% bullish. The bullish leg degrades faster historically; the methodology applies asymmetric scaling by design to bound that degradation. An unconfirmed assessment is not a wrong assessment; it is often one where the market was approaching the level but hadn't reached it within the window. For the worst 1% of misses, the deviation between the assessed value and the closest price the market actually reached is approximately 7% for bearish assessments and approximately 10% for bullish. The maximum observed deviation across the entire record is 8.0% bearish, 13.4% bullish.
Cohort and generalization
The empirical record derives from a defined cohort of 15 digital assets — 13 non-stablecoin and 2 stablecoin — comprising diverse market roles: established, large-capitalization assets; mid-capitalization and infrastructure assets; and gold-backed and fiat-backed value reference assets. The cohort was tested over an approximately two-year historical window spanning both expansion and contraction regimes. The same deterministic methodology applies to assets outside the cohort; per-asset empirical records accumulate as market history lengthens. For professionals presenting assessments in contested contexts, the methodology applies universally and the backtest record speaks directly to the cohort on which it was measured.
How to Read the Number
Wider gaps carry less conviction. The engine's bounded design dampens the assessment as the gap between SV and market price widens. Large SV–market gaps signal weaker structural conviction, not stronger — a bounded-output property of the methodology.
Market validation through price action. The intraday touches described under Validation are strong confirmations of the fair-value assessment — they show the assessed level is one the market is actively engaged with, not a theoretical estimate.
Built for professional timeframes. Structural Value is designed for professionals who assess value over weeks, months, and quarters — estate valuations, fund reporting, fiduciary due diligence, equitable distribution, and settlement analysis. It is not a trading signal.
Deterministic and auditable. The number is built to withstand professional scrutiny: a documented methodology, a complete audit trail, and a reproducible calculation path from input to output.
What You Receive
AIREPORT generates professional reports showing portfolio-level and per-asset structural valuations alongside integrity scores and risk events. Whether the report supports a settlement negotiation, a quarterly client review, or a fiduciary filing, the methodology is consistent and the audit trail is complete.