MacroRisk Sentinel is designed to help investors read the macro environment more clearly. It combines market-based signals, economic indicators, and historical context into a rules-based monitoring framework that is serious enough to be useful, but readable enough to use regularly.
Core indicators
6
Used in the main macro framework and in Crisis Similarity.
Additional indicators
3
Structural context indicators shown separately by design.
BTC/MSTR analytical tools
4
BTC and MSTR cycle outlooks plus BTC and MSTR valuation views.
The macro dashboard is built around 6 core indicators and 3 additional indicators. The core set drives the main macro read, while the additional set adds broader valuation, fiscal, and real-economy context.
Alongside that macro framework are 4 BTC & MSTR analytical tools: BTC Cycle Outlook, MSTR Cycle Outlook, BTC Realized Valuation, and MSTR Conservative Backing Premium. They complement the dashboard rather than redefine it.
This distinction is deliberate. The BTC & MSTR sleeve is not part of the core macro framework and is not included in Crisis Similarity, which remains focused on the most stable macro comparison set.
Start with the six core indicators as a group. They capture different parts of the macro environment: curve shape, valuation, market stress, labor conditions, recession sensitivity, and credit conditions. No single series should carry the full analytical burden.
Different indicators update on different cadences. Some move daily, some monthly, and some quarterly. A stale label often reflects the normal release schedule of the underlying series rather than a system failure or broken refresh process.
The risk bands are there to improve interpretability. They help show whether a reading is in a more normal, elevated, or stressed range relative to the framework. They are not promises, forecasts, or exact timing thresholds.
Each indicator below includes a concise interpretation guide and a compact methodology block showing the current framework inputs used for display.
Core indicators
Additional indicators
BTC & MSTR analytical tools
Source
FRED T10Y2Y
Frequency
Daily
Dashboard window
Last 30 days
Detail window
Last 1 year
Stale threshold
3 days
Risk bands
What it is
The spread between 10-year and 2-year U.S. Treasury yields. It is one of the most widely followed market-based signals for shifts in growth expectations and financial conditions.
Why it matters
A flatter or inverted curve has historically been associated with tighter conditions and weaker forward macro expectations.
How to interpret it
A clearly positive spread is generally more normal. A flat or negative spread points to more fragile macro conditions and deserves attention alongside the rest of the dashboard.
Source
Robert Shiller historical series
Frequency
Monthly history, fresher latest display when available
Dashboard window
Last 2 years
Detail window
Last 5 years
Stale threshold
45 days
Risk bands
What it is
A long-cycle valuation measure that smooths earnings through time. It is used to place current equity valuation conditions in historical context rather than to time short-term market moves.
Why it matters
Valuation does not drive every market move, but it matters for long-horizon return expectations and for judging whether the market is operating from a rich or more moderate starting point.
How to interpret it
Chart and history remain based on the canonical monthly Shiller series. The latest displayed value may use a daily market-based estimate derived from the latest S&P 500 level and the latest available Shiller denominator. That improves freshness between monthly releases, but it is not a new official Shiller monthly data point.
Source
FRED VIXCLS
Frequency
Daily
Dashboard window
Last 30 days
Detail window
Last 1 year
Stale threshold
7 days
Risk bands
What it is
The VIX is a market-based volatility measure derived from S&P 500 options. It is often used as a live gauge of stress, uncertainty, and repricing pressure.
Why it matters
When volatility expectations rise sharply, investors are usually reacting to stress, uncertainty, or a change in the perceived balance of risks.
How to interpret it
Lower readings usually align with calmer markets. Higher readings suggest more stress and more fragile sentiment, especially when confirmed by credit spreads or curve deterioration.
Source
FRED UNRATE
Frequency
Monthly
Dashboard window
Last 6 months
Detail window
Last 5 years
Stale threshold
45 days
Risk bands
What it is
A broad labor-market indicator tracking the share of the labor force that is unemployed. It is a core measure of macro resilience and labor demand.
Why it matters
The labor market sits near the center of the economic cycle. Persistent weakening here often confirms broader macro slowdown rather than isolated market stress.
How to interpret it
A low and stable rate usually supports an expansionary backdrop. A rising rate can indicate weakening labor conditions and slower economic momentum, especially when it is broad-based rather than noisy month to month.
Source
FRED RECPROUSM156N
Frequency
Monthly
Dashboard window
Last 6 months
Detail window
Last 5 years
Stale threshold
45 days
Risk bands
What it is
A recession-risk series published through FRED. It is a model-based macro signal rather than a directly traded market price.
Why it matters
It provides an additional lens on broad recession risk conditions and can help confirm whether other indicators are pointing to a more fragile macro backdrop.
How to interpret it
Higher readings indicate a more cautious macro regime. It is best read as part of a multi-indicator framework rather than as a standalone verdict.
Source
FRED BAA10Y
Frequency
Daily
Dashboard window
Last 6 months
Detail window
Last 5 years
Stale threshold
3 days
Risk bands
What it is
The spread between Moody's BAA corporate bond yield and the 10-year Treasury yield. It is a practical credit-stress measure.
Why it matters
Credit markets often register stress before it becomes obvious in slower macro data. Widening spreads can signal tighter financing conditions and rising risk aversion.
How to interpret it
Tighter spreads usually suggest healthier credit conditions. Wider spreads point to more stress in funding and credit markets, particularly when the move is persistent rather than temporary.
Source
FT Wilshire 5000 (Yahoo Finance) + U.S. GDP (FRED)
Frequency
Daily market side, quarterly GDP denominator
Dashboard window
Last 2 years
Detail window
Last 5 years
Stale threshold
3 days
Risk bands
What it is
A broad valuation context measure comparing market size with the size of the economy.
Why it matters
It offers a high-level way to judge whether the market appears modest, elevated, or stretched relative to underlying economic scale.
How to interpret it
Current values use FT Wilshire 5000 market data and the latest available quarterly U.S. GDP. The market side may update more frequently than the GDP denominator, so short-term moves can reflect market changes before the macro denominator refreshes.
Source
FRED GFDEGDQ188S
Frequency
Quarterly
Dashboard window
Last 1 year
Detail window
Last 10 years
Stale threshold
120 days
Risk bands
What it is
Federal debt as a share of GDP. It is a structural fiscal context indicator rather than a fast-moving market signal.
Why it matters
It helps frame fiscal flexibility, long-run balance sheet pressure, and the broader policy backdrop around debt and growth.
How to interpret it
Higher levels do not automatically imply immediate market stress, but they matter for long-run fiscal resilience and should be read as part of the structural macro backdrop.
Source
FRED INDPRO
Frequency
Monthly
Dashboard window
Last 2 years
Detail window
Last 6 years
Stale threshold
45 days
Risk bands
What it is
A broad measure of U.S. industrial output, including manufacturing, mining, and utilities. It adds real-economy production context to the dashboard.
Why it matters
It helps distinguish between market-driven stress and genuine weakening in cyclical production activity.
How to interpret it
Stronger levels suggest firmer production conditions. Weakening levels can indicate softer industrial momentum, especially when confirmed by labor, credit, or curve signals.
Possible Cycle Low and Possible Cycle Top ranges with separate timing and evidence-strength context.
Model
BTC Cycle Outlook v1
Purpose
Estimates plausible Bitcoin Cycle Low and Cycle Top price ranges together with separate timing windows.
Price output
A modelled P20–P80 range with a secondary P50 central estimate.
Timing
Each event has its own modelled timing window.
Confidence
Evidence strength, not the probability that the range will occur.
What it is
A frozen ensemble model that presents a Modelled range (P20–P80), a Central estimate (P50), and a separate Timing window for each possible cycle event.
Why it matters
It gives long-term investors a disciplined way to separate plausible price ranges, timing, and the strength of supporting evidence.
How to interpret it
Read Modelled range, Central estimate, Timing, and Evidence strength separately. Status may be Active, Provisional, Reduced coverage, Stale, Window passed, or Invalidated.
Long-term price structure
Bitcoin's long-run price behaviour and how current and future cycle levels relate to that broader structural trajectory.
Cycle compression
How Bitcoin's historical cycle gains and drawdowns have changed across successive market cycles.
On-chain cost basis
Holder cost-basis and valuation information derived from Bitcoin's on-chain market structure, including Realized Price relationships.
Cycle timing
Historical cycle timing together with the Bitcoin halving schedule and event-specific timing windows.
Cross-model confirmation
Whether the available model components broadly agree, their evidence remains robust, required inputs are available, and the underlying data is sufficiently fresh.
BTC Cycle Outlook does not rely on a single model in isolation. The published range combines multiple distinct model components, so the final outlook reflects several different views of Bitcoin's cycle structure rather than one indicator or formula.
A model component may become unavailable when the specific input required by its methodology does not yet exist or is not sufficiently reliable. The remaining available components are handled according to the frozen v1 publication rules.
Evidence strength evaluates the quality and completeness of the evidence behind the published outlook. It is not a probability score.
Model coverage
How much of the intended model set is currently available.
Timing support
How strong the model's timing evidence is for the event being assessed.
Model agreement
How closely the active model components support a similar overall conclusion.
Robustness
How stable the outlook remains under the model's built-in sensitivity checks.
Evidence quality
How clearly and reliably the available evidence supports the model components used in the current state.
Data freshness
Whether the required market, on-chain, and timing inputs are current enough to support a live outlook.
Forecast horizon
How far the forecasted event is from the current observation point.
Why HIGH does not appear in v1
Frozen BTC Cycle Outlook v1 intentionally limits Evidence strength below HIGH because the historical evidence base is still limited. Cycle Low is capped at 0.64 and Cycle Top at 0.69, while HIGH begins at 0.70. Therefore MODERATE is the strongest possible Evidence strength label in v1.
These caps are part of the frozen v1 methodology and do not increase automatically as an event date approaches.
Maps the BTC Cycle Outlook into conservative MSTR backing per assumed diluted share using Strategy's current corporate structure.
Purpose
Translate BTC Cycle Low and Cycle Top scenarios into conservative MSTR backing per assumed diluted share.
Output
Lower, central and upper conservative backing estimates.
Timing
Inherited from the corresponding BTC Cycle Outlook mapping window.
Market premium
Not included in the current model.
Mapping confidence
Low.
What it is
MSTR is economically different from BTC because one MSTR share represents an interest in Strategy's BTC holdings, its financing structure, preferred claims, USD Reserve, and dilution/share count. The model therefore maps each BTC scenario through the current corporate structure rather than simply multiplying BTC price by a fixed ratio.
How Conservative Backing is calculated
Conservative Backing per share = (BTC scenario value + Strategy USD Reserve − convertible debt − preferred claims) / assumed diluted shares
BTC scenario value = BTC scenario price × Strategy BTC holdings
This is the same USD-Reserve-only backing definition used by the MSTR Conservative Backing Premium card, applied to each BTC scenario. USD Cash is intentionally excluded as discretionary Bitcoin-treasury liquidity.
Scenario mapping
The BTC lower scenario maps to an MSTR lower backing estimate, the BTC central scenario to a central backing estimate, and the BTC upper scenario to an upper backing estimate.
MSTR outputs are not labelled P20/P50/P80, because the BTC scenario percentiles do not become an independent MSTR probability distribution.
Current conservative backing
The dashboard may also show a separate "Current conservative backing" reference, based on current BTC market value and current Strategy corporate inputs. This is context only — it is not the MSTR market price, it does not alter the Cycle Outlook mapping, and it simply helps investors compare today's backing environment with the scenario backing ranges.
Why market premium is excluded
MSTR market price can trade at a premium or discount to Conservative Backing. Historical premium behavior was explicitly studied for the current model: LOW evidence was insufficient, and TOP evidence was informative but not robust enough for production application. Rather than introduce false precision, the current model intentionally stops at backing rather than forecasting a market premium. This is a deliberate modelling boundary, not missing functionality.
Timing
MSTR Cycle Outlook has no independent timing engine. The LOW and TOP windows come directly from BTC Cycle Outlook, so the dashboard identifies them as BTC mapping windows.
Confidence
Mapping confidence is Low in the current model. This reflects evidence quality, not event probability — no synthetic percentage confidence score is created.
High leverage / non-positive backing
If the lower scenario produces non-positive backing but the central estimate remains positive, the lower estimate is not published and "High leverage risk" is shown instead. If the central backing itself is non-positive, that event is not published at all.
What it is NOT
Data and refresh
BTC scenario inputs come from BTC Cycle Outlook; corporate inputs come from validated Strategy data. The mapping refresh checks automatically, but the numerical mapping is recalculated only when relevant BTC, model, or corporate inputs actually change — a routine scheduler check does not by itself create a new mapping.
This sleeve provides Bitcoin and Strategy-specific valuation, on-chain, and common-equity structural context alongside the broader macro dashboard. It is complementary by design and remains separate from Crisis Similarity.
Signal summary
Group
BTC/MSTR analytical signal
Coverage
Market-based daily snapshot
Data cadence
Daily
Source
Coin Metrics Community API
Interpretation framework
Valuation
What it is
BTC Realized Valuation separates a canonical daily layer from a current display overlay. Canonical daily layer: Coin Metrics daily PriceUSD, Coin Metrics daily CapMVRVCur, and Realized Price derived from that same completed daily observation. Current display overlay: when a validated intraday BTC market price is available from the existing BTC market lane, the displayed current MVRV overlay = intraday BTC market price / latest daily Realized Price, and the displayed vs-realized % derives from that overlay; the existing valuation thresholds apply to this current overlay MVRV. This is not a new Coin Metrics intraday MVRV series — canonical Coin Metrics CapMVRVCur remains the underlying daily source observation. Daily fallback: if intraday market data is unavailable, the card uses the canonical daily BTC price and canonical daily MVRV directly. Raw MVRV is used as a valuation measure relative to realized cost basis, not as a standalone cycle-phase classifier or price forecast.
Why it matters
It helps show whether Bitcoin is trading close to aggregate on-chain cost basis or at a more extended valuation, using a single MVRV-based valuation reading.
How to interpret it
Valuation hero. The hero percentage shows how far market value sits above or below realized value: (MVRV − 1) × 100. The MVRV ratio directly below it shows the same relationship in multiple form.
Valuation status. The valuation status label maps the same MVRV reading onto the fixed bands above: Depressed, Fair Value Zone, Elevated, or Overheated.
BTC Context. Historical Stretch (MVRV Z) and Issuance are shown as supporting on-chain context alongside the valuation reading.
Contextual analysis — not a price forecast or standalone market-timing model.
How MVRV and MVRV Z differ
MVRV measures the ratio between Bitcoin's market value and realized value. It describes the current valuation gap relative to the network's aggregate realized cost basis.
MVRV Z uses the same market-versus-realized-value gap but normalizes it against Bitcoin's historical market-cap volatility. This helps distinguish an ordinary valuation gap from one that is historically unusual.
MacroRiskSentinel uses raw MVRV as a valuation measure, not as a standalone cycle-phase classifier. MVRV Z is shown only as historical stretch context; it is related to raw MVRV rather than an independent signal.
MVRV Z — realized cap = market cap / MVRV; Z = (market cap − realized cap) / expanding population standard deviation of market cap (population standard deviation, ddof = 0). Method version: mvrv_z_classic_v1_pop.
BTC Issuance Multiple
BTC Issuance Multiple measures the daily USD value of newly issued Bitcoin relative to its own trailing one-year average.
IssTotUSD divided by its trailing 365-day mean IssTotUSD (inclusive of the current complete day); transaction fees excluded. Method version: puell_btc_issuance_v1.
Dashboard display: (BTC Issuance Multiple − 1) × 100, shown as the percentage above or below the trailing 1-year average. Example: 1.13x → +13%. This is a display transformation only, not a different model.
Automated interpretation
The 'What This Means' text on the dashboard is generated deterministically from displayed values using fixed templates — it is not produced by an LLM and is not an investment recommendation.
MVRV-Z narrative bands are presentation copy only, not a new signal model: below 0.00 is below the long-run center; 0.00 to under 2.00 is modest; 2.00 to under 5.00 is elevated; 5.00 to under 7.00 is very high; 7.00 and above is near the strongest historical extremes.
MVRV-Z classification uses the displayed two-decimal value, not the raw unrounded figure.
Issuance above/below wording is derived from the canonical BTC Issuance Multiple's rounded dashboard transform.
Signal summary
Group
BTC/MSTR analytical signal
Coverage
Dashboard signal
Data cadence
Hourly market refresh; corporate-state inputs update on Strategy's disclosure/data cadence
Source
Strategy corporate disclosures, share data, and market pricing inputs
Interpretation framework
Valuation
Backing Trend
What it is
MSTR Conservative Backing Premium combines two separate views of Strategy common equity. Valuation compares MSTR's market price with a simplified conservative Bitcoin-backed value per assumed diluted share, where conservative backing = BTC value + Strategy USD Reserve − convertible debt − preferred claims. USD Reserve is included because Strategy designates it to support preferred dividends and debt interest; USD Cash is intentionally excluded as discretionary Bitcoin-treasury liquidity — Strategy's own broader USD Assets / Net BPS / mNAV framework includes both, so this measure is intentionally more conservative and is not Strategy's official Net BPS or mNAV. Backing Trend measures whether claims-adjusted conservative backing per assumed diluted share improved or deteriorated between two valid distinct corporate states. The claims-adjusted measure incorporates BTC holdings, USD Reserve, convertible debt, preferred claims, and assumed diluted shares. Both corporate states are valued using the same frozen BTC reference price captured when the newer state is established, so ordinary BTC market-price movement does not itself create the trend.
Why it matters
The signal separates three questions an investor should not confuse: what premium or discount the market currently pays relative to conservative backing; whether gross BTC exposure per diluted share is improving; and whether residual conservative common-equity backing per diluted share is improving after senior financing claims. BTC/share can improve while claims-adjusted common backing does not improve proportionally if senior claims increase.
How to interpret it
Valuation. Backing per share represents simplified conservative common backing divided by assumed diluted shares. The Backing Multiple compares MSTR market price with that backing.
Claims-adjusted trend. The primary Backing Trend compares conservative backing per share between two valid corporate states using one frozen BTC reference price.
BTC/share trend. BTC per diluted share remains a supporting gross-exposure KPI and does not account for debt, preferred claims, USD Reserve, or USD Cash.
What drove the move. BTC holdings, diluted shares, and senior claims help explain the difference between gross BTC/share accretion and claims-adjusted common-equity accretion.
Senior claims burden. Shows debt and preferred claims net of USD Reserve per BTC held; lower is better.
Market valuation can refresh hourly. Corporate-state history changes only when Strategy's economic corporate state actually changes, so Backing Trend does not move merely because BTC or MSTR market prices move intraday.
The comparison uses two valid distinct corporate states, using a genuine validated disclosure date when available and otherwise the first validated observation of a new economic state — not necessarily two official Strategy disclosures. The feature is prospective where historical coherent claims data are unavailable.
Claims-adjusted backing is a derived analytical measure — not accounting book value, not liquidation value, not Strategy's official Net BPS or mNAV, and not a price forecast.
Simplified analytical lens — not a full NAV/company valuation model or liquidation threshold.
Automated interpretation
The 'What This Means' text on the dashboard is generated deterministically from displayed values using fixed templates — it is not produced by an LLM and is not an investment recommendation.
The existing premium band (Deep Discount, Near Backing, Moderate Premium, Extreme Premium, or the High Leverage Risk override) remains the canonical classification; the summary only restates it.
A next-band sentence appears only when the current multiple is within 0.05x of the next threshold, or sits in the upper 20% of its current bounded band.
When Conservative Backing per share is not positive, the summary states that the premium multiple is not a meaningful valuation reading instead of computing one.
BTC per assumed diluted share is presented as a factual structural figure only.
Senior Claims Burden receives no automatic high/low/safe classification.
Crisis Similarity compares the current environment with prior historical stress regimes. It is built from the 6 core indicators only. The additional indicators are excluded by design so the framework remains focused on the most stable and decision-relevant comparison set.
The purpose is contextual resemblance, not prediction. In plain terms, the feature asks: what does the current macro profile most resemble? It does not ask whether a crisis is about to happen, and it should not be read as a probability forecast.
CAPE within Crisis Similarity continues to rely on canonical Shiller monthly history rather than the fresher daily display overlay. That preserves consistency in the historical comparison framework. The result is a contextual reference tool, not a prediction engine.
What it is for
A structured resemblance framework that helps investors place current conditions alongside known historical stress patterns.
External data is ingested into internal observations, and the dashboard, detail views, and similarity outputs are built from internal cached data rather than raw provider calls on every page load.
The framework is rules-based and designed for consistency and interpretability. It aims to deliver stable monitoring outputs with clear definitions, understandable signals, and disciplined presentation, while keeping implementation-specific internals private.