Crypto Macro Economics Report
A quantitative regime-scoring framework that translates macro and liquidity indicators into actionable crypto portfolio positioning guidance.
TL;DR
The Macro Economics Report ingests 13 macro and liquidity indicators from trusted sources (BIS, FRED, and others), converts them into a single interpretable regime score, and translates that score into actionable crypto portfolio positioning across four risk buckets: Stablecoins, Majors (BTC/ETH), High-beta alts, and Micro/long-tail assets. The framework provides institutional-grade guidance for sizing these risk buckets in the current regime, with its primary role being to support systematic allocation decisions.
How to use it (Web UI)
The Macro Economics Report provides a structured workflow: personalize your report, view the analysis, and use the shareable link to revisit or compare changes over time.
1) Personalize your report
Choose your preferred language from the dropdown menu and select a report type from the available options. Then click "Open report" to view your personalized macro economics analysis. Reports are generated every 24 hours using the latest data from trusted sources (BIS, FRED, DeFiLlama, SoSoValue) and compute the current regime score.
2) Share or revisit
Each report produces a shareable analysis link so you can return later or compare regime changes over time.
3) Read the report top-down
- Executive Summary: Current regime overview, effective score, and positioning guidance with risk budget recommendations.
- Economic Indicators (Base Score): Weighted table of 13 macro and liquidity KPIs with current values and contributions to the base score.
- Current Events Overlay: Qualitative adjustments (policy, fiscal stress, liquidity, sentiment) that modify the base score.
- Portfolio Positioning: Recommendations for sizing risk buckets (Stablecoins, Majors, High-beta alts, Micro/long-tail).
- Scenarios & Triggers: Bull/base/bear paths with testable conditions for regime transitions.
What the Macro Economics Report does (high level)
The report combines multi-source macro data, computes weighted regime scores, applies qualitative adjustments from current events, and produces actionable portfolio positioning guidance.
1) Data ingestion (trusted sources, normalized)
We pull a best-effort blend of macro and liquidity indicators from authoritative sources:
- Global liquidity: BIS global liquidity aggregates (USD credit to residents and non-residents, plus Fed balance sheet).
- Monetary policy: FRED Federal Funds Rate, yield curve spreads, TIPS real yields.
- Inflation: FRED US CPI (year-over-year).
- USD plumbing: FRED Reverse Repo Volume, Treasury General Account balance.
- Risk sentiment: FRED S&P 500, VIX volatility index.
- Crypto-specific liquidity: DeFiLlama stablecoin market cap, SoSoValue US spot ETF flows (BTC+ETH).
2) KPI computation & regime classification
Each of the 13 indicators is:
- Normalized into a consistent schema with current value, previous value, and period-specific deltas (absolute and percentage).
- Classified into a regime signal: R+ (risk-on), N (neutral), or R- (risk-off) based on indicator-specific thresholds and directional logic.
- Weighted according to its importance in the overall regime assessment (weights sum to 100%).
3) Base score aggregation
The base score (BS) is computed as a weighted sum of KPI regime signals:
- Each KPI contributes its weight × regime_score (where regime_score is -1, 0, or +1).
- The result is normalized to a [-1, +1] scale.
- Coverage tracking ensures we only aggregate when sufficient data is available.
4) Qualitative adjustment overlay
Current events and structural factors adjust the base score:
- Central bank policy: Rate cut cycles, forward guidance, policy credibility.
- Fiscal sustainability: Debt levels, interest payments, refinancing needs.
- Funding liquidity: Reverse repo spikes, stablecoin flows, cash hoarding signals.
- Labor market: Unemployment trends, payroll growth, wage pressures.
- Consumer sentiment: Conference Board confidence, spending patterns, recession signals.
- Crypto-specific: Liquidations, stablecoin withdrawals, ETF flow reversals.
Each adjustment component includes a factor name, finding, component adjustment, and research evidence. The qualitative adjustment (QA) is the sum of component adjustments, capped to [-0.50, +0.50].
5) Effective score & regime labels
The effective score (ES) = Base Score (BS) + Qualitative Adjustment (QA), clamped to [-1.0, +1.0].
Effective regime labels (5 levels):
- R++ (Strong Risk On) if ES ≥ 0.50
- R+ (Risk On) if 0.25 ≤ ES < 0.50
- N (Neutral) if -0.25 ≤ ES < 0.25
- R- (Risk Off) if -0.50 ≤ ES < -0.25
- D (Defensive) if ES < -0.50
6) Portfolio positioning guidance
The report translates the effective regime into actionable allocation recommendations:
- Stablecoins: Dry powder allocation (e.g., 25–35% in neutral-to-defensive regimes).
- Majors (BTC/ETH): Core crypto exposure with lower volatility than alts.
- High-beta alts: Higher-volatility assets that benefit from risk-on regimes.
- Micro/long-tail assets: Highest-risk, highest-reward exposure for strong risk-on regimes.
Positioning guidance includes explicit percentage ranges for each bucket, beta adjustments, rationale tied to the current regime drivers, and testable trigger conditions for regime transitions.
7) How we summarize it (without "black box" magic)
The report combines deterministic computations (weighted KPI aggregation, qualitative adjustments, effective score calculation) with a structured narrative that explains the current regime and its drivers, portfolio positioning recommendations with explicit risk budget sizing, bull/base/bear scenarios with testable trigger conditions, and limitations when data coverage is incomplete.
The 13 Macro Indicators
Our framework analyzes 13 weighted indicators across global liquidity, dollar strength, rates & policy, inflation, USD plumbing, risk sentiment, and crypto-specific factors.
Global Liquidity (25% total weight)
Dollar Strength (10% total weight)
Rates & Policy (20% total weight)
Inflation (5% total weight)
USD Plumbing (20% total weight)
Risk Sentiment (14% total weight)
Crypto Specific (6% total weight)
KPI Weighting Rationale
The 13 indicators are weighted according to their systematic importance in driving crypto market regimes. The weighting philosophy prioritizes systemic liquidity drivers, policy transmission mechanisms, risk sentiment proxies, and crypto-specific factors.
Weight Distribution by Category
Global Liquidity (USD) YoY — 15%: The highest single weight reflects that liquidity is the primary driver of crypto markets. Research shows that global liquidity expansions correlate strongly with Bitcoin and crypto asset performance. This indicator captures the broadest measure of USD credit availability across the global financial system, making it the most systematic driver of risk asset regimes.
Fed Balance Sheet (4w) — 10%: Fed balance sheet expansion/contraction directly injects or drains system liquidity. While important, it's weighted lower than global liquidity because it's a single central bank's actions within a broader global system, and its impact can be offset by other factors.
Reverse Repo Volume (20d) — 10%: Spikes in reverse repo usage signal acute short-term funding stress and collateral scarcity. This is a leading indicator of liquidity crises and risk-off positioning, making it critical for regime detection.
Treasury General Account Balance (4w) — 10%: Treasury cash movements can inject or drain hundreds of billions in liquidity from the banking system. When the TGA rises, it drains liquidity; when it falls (spending), it injects liquidity. This mechanical relationship makes it a key systematic driver.
Broad US Dollar Index (20d_vs_ma20) — 10%: A strong dollar tightens global financial conditions, making dollar-denominated debt more expensive and pressuring risk assets globally. This is weighted at 10% because dollar strength is a persistent headwind when elevated, but its impact is often transmitted through other indicators (liquidity, rates).
Federal Funds Rate (90d) — 8%: The policy rate directly affects funding costs and risk-free returns, making it a core transmission mechanism. Weighted at 8% because while important, its impact is often already reflected in liquidity conditions and yield curve shape.
Yield Curve (10Y–2Y Spread) — 7%: The yield curve is a leading indicator of growth expectations and recession risk. An inverted curve (negative spread) has historically preceded recessions and risk-off regimes. Weighted at 7% because it's predictive but less directly actionable than current policy rates.
10Y TIPS Real Yield — 5%: Real yields represent the inflation-adjusted return on safe assets. Higher real yields increase the opportunity cost of holding risk assets like crypto. Weighted at 5% because it's a secondary effect (derived from nominal yields and inflation expectations) rather than a primary driver.
US CPI Inflation (YoY) — 5%: Inflation affects policy decisions and real yields, but its impact is indirect and already captured through policy rates and TIPS yields. Weighted at 5% because it's a constraint on policy rather than a direct driver of risk asset regimes.
S&P 500 (60d) — 8%: Equity momentum reflects broader risk sentiment and often leads crypto markets. Weighted at 8% because it's a reliable proxy for risk-on/risk-off behavior, though it can be noisy in the short term.
VIX Volatility Index — 6%: VIX measures equity market stress and fear. Higher VIX often corresponds to risk-off behavior and crypto deleveraging. Weighted at 6% because it's a sentiment indicator that can spike temporarily without regime change.
Stablecoin Liquidity (USD Market Cap) (30d) — 4%: Crypto-native liquidity is important but reactive. Stablecoin supply tends to grow during risk-on regimes and contract during risk-off, making it more of a confirmation signal than a leading indicator. Weighted at 4% because it reflects rather than drives regime changes.
US Spot ETF Net Flows (BTC+ETH) (5d_sum) — 2%: ETF flows are highly reactive to price movements and sentiment, often following rather than leading regime changes. Weighted at only 2% because while they provide useful confirmation of institutional sentiment, they are too short-term and reactive to be a primary regime driver.
Weighting Philosophy Summary
The weighting scheme reflects a hierarchical view of macro drivers:
- Systemic liquidity (45% combined): Global liquidity, Fed balance sheet, and USD plumbing indicators together capture the fundamental availability of capital that drives all risk assets, including crypto. This is the foundation of the regime framework.
- Policy transmission (20%): Rates and yield curve indicators capture how monetary policy affects funding costs and growth expectations. These are important but secondary to liquidity conditions.
- Risk sentiment (14%): Equity markets and volatility provide real-time signals of market psychology, but they are more reactive than predictive.
- Crypto-specific (6%): While stablecoin liquidity and ETF flows are directly relevant to crypto markets, they are weighted lower because they tend to confirm rather than lead regime changes. They are useful for validation but not primary drivers.
- Supporting indicators (15% combined): Dollar strength, inflation, and real yields provide important context but are often already reflected in the primary drivers above.
This weighting ensures that the base score prioritizes systematic, predictive drivers over reactive, crypto-specific signals, creating a framework that can identify regime changes before they fully manifest in crypto markets.
Conceptual Framework
The Macro Economics Report sets the risk budget at the portfolio level (segment sizing across stables/majors/high-beta/micro-caps), while:
- Narrative and sentiment work identify "which sectors" (for example, RWA, Privacy, AI).
- Due diligence engines drive "which tokens" within those sectors.
This separation ensures that macro regime assessment informs allocation sizing decisions independently of sector selection and token-level analysis.
Frequently Asked Questions
Is this financial advice?
No. This is a data-processing tool designed for educational research. Always perform your own due diligence.
What data sources does the report use?
We pull data from trusted sources including BIS (Bank for International Settlements), FRED (Federal Reserve Economic Data), DeFiLlama for stablecoin metrics, and SoSoValue for ETF flow data.
How often is the data updated?
Reports are generated every 24 hours using the latest data from trusted sources (BIS, FRED, DeFiLlama, SoSoValue). Each report reflects the most recent available data at the time of generation.
Can I share my macro economics reports?
Yes. Each analysis generates a shareable link that you can bookmark or share with others. Reports are persistent and can be revisited later to compare regime changes over time.
Disclaimer
The Macro Economics Report uses best-effort data retrieval from trusted sources and automated analysis. Data may be incomplete or delayed, and interpretations can be wrong. This is for educational purposes only and is not financial advice.