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Raoul Pal's Liquidity Framework: The Everything Code

Understand Raoul Pal's macro thesis—how liquidity, refinancing cycles, and fiat debasement are proposed to connect asset markets.

Jan Herbst
First published 20 Jan 2026
Last verified 20 Jan 2026
8 min read

What You'll Learn

  • Understand Raoul Pal's core liquidity thesis
  • Understand the framework's model-dependent debasement hurdle concept
  • See how Pal connects liquidity to all risk assets
  • Recognize the critiques and limitations of the framework

Raoul Pal is one of the most influential macro investors of the past decade. His framework—"The Everything Code"—argues that liquidity is the master variable driving all asset prices.

This article explains his core ideas and how VantMacro incorporates them into regime analysis.

Disclaimer: This is educational content explaining Pal's publicly stated views. It is not investment advice or an endorsement of any specific strategy.

Who is Raoul Pal?

Raoul Pal is the founder of Real Vision and Global Macro Investor. His background includes:

  • Former head of European equity hedge fund sales at Goldman Sachs
  • Retired from finance at 36 after successful macro trading
  • Pioneer in economic video content (Real Vision, 2014)
  • Prominent advocate for Bitcoin and crypto assets

His influence stems from consistently explaining complex macro concepts in accessible terms.


The Everything Code

Pal's central framework is "The Everything Code"—a unifying thesis connecting liquidity, debt cycles, and asset prices.

Core Idea

Post-2008, central banks engineered a "perpetual debt jubilee" through quantitative easing (QE) and low interest rates. The result:

  1. Debt Refinancing Cycle — Government refinancing is proposed to create a recurring liquidity pulse; the repository has not calibrated a fixed period
  2. Liquidity = Master Variable — Changes in central bank balance sheets and money supply (M2) drive all risk assets
  3. Fiat Debasement — The system is argued to erode purchasing power over time

The Debasement Hurdle

Pal's framework combines a chosen liquidity-growth measure with a chosen inflation measure to define a purchasing-power hurdle. VantMacro does not embed a fixed annual rate because the result changes with currency, series, transform, sample, and aggregation rule. A numerical hurdle must be computed from a declared input set rather than copied from the framework narrative.


Liquidity as Primary Alpha

In Pal's view, liquidity is the alpha in modern markets:

Why Liquidity Matters

  • QE injects reserves — When central banks buy bonds, they credit banks with new reserves, creating money that flows into financial assets
  • Asset prices float on liquidity — Prices rise not because of fundamentals, but because more money chases the same assets
  • Correlation can be high — but the reported strength depends on the liquidity definition, the lag choice, and the sample window

M2 vs Fed Balance Sheet

Legacy exploratory scripts tested the broad “liquidity drives prices” thesis with log-level regressions. Those outputs are not in the canonical generated pipeline, and level-on-level fits can be spurious when both series trend. No fixed R² is therefore published here as validated evidence.

Why track components separately anyway?

  • M2, central bank balance sheets, and net-liquidity “drains” (TGA/RRP) can move in different directions
  • Collapsing them into a single composite can hide offsetting forces

The Practical Application

Watch both M2 YoY and Fed balance sheet YoY separately:

SignalM2 YoYFed BS YoYInterpretation
Strong bullishRisingRisingMaximum risk-on
BullishRisingFallingSelective risk-on
NeutralMixedMixedWait for clarity
BearishFallingRisingUnusual; watch closely
Strong bearishFallingFallingDefensive positioning

Liquidity Regimes

Pal's framework interprets positive liquidity growth as expansion and negative growth as contraction. Stronger bands sometimes appear in presentations, but VantMacro does not reproduce them as calibrated cutoffs. The maintained product shows the computed magnitude and uses a disclosed operational zero crossing.

Key Insight

Don't fight the liquidity cycle.

When the Fed, ECB, and BoE are all easing simultaneously, risk assets historically deliver extraordinary returns. When all three tighten together, even "fundamentally strong" assets suffer.


Assets in Pal's Framework

Pal divides assets into those that benefit from debasement and those that are debased:

Assets That Beat Debasement

  1. Bitcoin/Crypto — Hardest money, limited supply, benefits from liquidity expansion
  2. Tech equities — High beta to liquidity, compound faster than debasement
  3. Select growth stocks — Those with strong network effects and pricing power

Assets That Merely Preserve

  1. Real estate — Keeps pace with inflation but rarely beats debasement after costs
  2. Gold — Store-of-value thesis with period-dependent realized returns
  3. Bonds — Return capital, but negative real returns in debasement environment

Assets That Are Debased

  1. Cash — Loses purchasing power when its return trails the selected inflation measure
  2. Low-yield savings — Same problem
  3. Low-margin businesses — Unable to pass through inflation

Criticisms and Caveats

Pal's framework isn't without criticism:

1. The Debasement Hurdle Is Model-Dependent

The exact rate of debasement varies by:

  • Time period measured
  • Currency (USD, EUR, etc.)
  • Definition of inflation used

Different defensible definitions can produce materially different rates. No single value is treated as canonical here.

2. Correlation ≠ Causation

Yes, liquidity and asset prices are correlated. But:

  • Both may respond to a third factor (e.g., confidence, growth expectations)
  • The relationship has varied in strength over different periods
  • Forward correlations are weaker than backward-looking ones

3. Bitcoin Is Not Guaranteed

Pal is famously bullish on Bitcoin, but:

  • It has experienced severe historical drawdowns
  • Regulatory risk remains material
  • The "hardest money" thesis is contested

4. The Framework May Break

If central banks ever genuinely normalize policy (unlikely but possible), the liquidity-drives-everything thesis may weaken.


How VantMacro Uses This

VantMacro incorporates elements of Pal's framework while maintaining empirical rigor:

What We Adopt

  1. M2 and Fed balance sheet tracked separately — Separate series avoid hiding offsetting moves; no superiority claim is made without a declared generated comparison
  2. Liquidity as a regime dimension — One of three dimensions in composite regime classification
  3. YoY changes prioritized — Direction matters more than absolute levels

What We Temper

  1. No fixed return hurdle — Any purchasing-power comparison must use declared, current inputs
  2. Balanced perspective — Liquidity is one factor, not the only one
  3. Generated evidence with limits — The current regime artifacts publish sample counts and a descriptive median-date comparison; classifier accuracy and causal liquidity claims are not calibrated

View Liquidity Dashboard →


Key Takeaways

  1. Liquidity is a primary driver of risk asset returns in the post-2008 era

  2. Track M2 and Fed balance sheet separately — They have different relationships with assets

  3. The debasement thesis — Fiat currencies are structurally debased; assets must beat this hurdle

  4. Don't fight the cycle — When central banks ease in concert, risk-on; when they tighten in concert, defensive

  5. Apply with nuance — Pal's framework is a lens, not gospel; always combine with other signals


Data Sources

  • Primary framework sources: Raoul Pal’s public writing and presentations (Real Vision / Global Macro Investor) describing the “Everything Code” thesis.
  • Empirical checks referenced here use standard public macro/liquidity series (e.g., broad money and central bank balance sheets) and public asset price history.

Methodology

  • Separates “levels” vs “changes”: levels regressions can show high R² due to shared trends, so VantMacro sanity-checks both levels and YoY-style variants.
  • Treats liquidity as a slow-moving backdrop variable. The current canonical regime pipeline recomputes its descriptive stability split at the median classified date; it is not an untouched out-of-sample test.

Limitations

  • High explanatory power on price levels does not imply causality or tradable predictability (trend co-movement is a major confound).
  • Liquidity definitions vary (M2 vs balance sheet vs composites); results can change materially with series choice, lag choice, and sample window.
  • Frameworks are narratives unless operationalized and validated; use as context, not as a mechanical allocation rule.

Further Reading


See Liquidity Frameworks on VantMacro

VantMacro's Frameworks page includes:

  • Raoul Pal's Everything Code summary
  • Julien Bittel's Macro Seasons
  • Jordi Visser's AI Macro Nexus
  • Current positioning implications

Explore Frameworks →

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The information provided by VantMacro is for educational and informational purposes only and should not be construed as financial, investment, legal, or tax advice.

Not Financial Advice: VantMacro provides economic data, regime analysis, and historical performance metrics. We do not recommend specific securities, investment strategies, or portfolio allocations. All content is for general information and should not be relied upon for making investment decisions.

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About the Author

Jan Herbst is the founder of VantMacro, an empirically-grounded macro intelligence platform. He specializes in global liquidity analysis, market regime detection, and business cycle tracking.

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