The methodology behind the Net Liquidity framework
Net Liquidity = Fed Balance Sheet − TGA − ON RRP
Total assets held by the Federal Reserve, including Treasury securities and mortgage-backed securities. When the Fed buys assets (QE), this number grows and injects liquidity into the system.
The US government's checking account at the Federal Reserve. When the Treasury accumulates cash (e.g., after debt issuance), it drains liquidity from the private sector. When it spends, liquidity is released back into the system.
Cash parked at the Fed overnight by money market funds and other counterparties. This represents liquidity that exists but is temporarily removed from productive circulation in the financial system.
Net Liquidity measures the actual amount of cash available to flow through the financial system at any given time. While the Fed's balance sheet represents the total pool of assets the central bank holds, not all of that translates into usable liquidity. The Treasury General Account and the Overnight Reverse Repo facility act as drains, pulling cash out of circulation and reducing the amount available for lending, investing, and speculation.
When net liquidity rises, there is more cash chasing assets. Banks have more reserves, money market conditions are loose, and risk appetite increases across the board. Conversely, when the TGA swells (Treasury building a cash buffer) or the RRP facility absorbs excess reserves, the effective liquidity reaching Wall Street and Main Street shrinks, even if the Fed's balance sheet hasn't changed.
Historically, changes in net liquidity have shown a strong correlation with risk-asset prices, including equities (S&P 500, Nasdaq), Bitcoin, and credit markets. Major drawdowns in net liquidity have preceded or coincided with market selloffs, while periods of expanding liquidity have fueled rallies. This is why institutional desks track this metric daily and why it forms the foundation of our regime classification system.
Our model classifies the current macro environment into one of four regimes based on liquidity conditions, rates, and financial stress indicators.
Net liquidity is rising, credit spreads are tight, and the yield curve is steepening. Risk assets tend to perform well as abundant liquidity flows into equities, crypto, and credit.
Net liquidity is falling as the Fed hikes rates or reduces its balance sheet. The yield curve inverts. This is the warning phase before broader market stress.
Net liquidity growth turns negative. Credit spreads widen significantly, recession risk rises, and risk assets face sustained selling pressure.
The Fed is pivoting toward accommodation. Net liquidity inflects upward, spreads stabilize, and markets begin pricing in recovery before the data confirms it.
Directional momentum of the liquidity aggregate
Spread between 10-year and 2-year Treasury yields
ICE BofA HY index spread over Treasuries
Broad money supply growth rate
Chicago Fed National Financial Conditions Index
BLS U-3 unemployment rate
Input your holdings. Get a regime-aligned action plan showing how your portfolio maps to current macro conditions and where adjustments may be warranted.
Enter your tickers and dollar amounts. The engine automatically classifies each asset (equity, crypto, gold, credit, commodities, cash) by looking up what the company or fund actually does.
Your portfolio is scored 0-100 against the optimal allocation for the current regime. A score of 38 in contraction means you are heavily exposed to assets that historically lose money in this environment.
The engine generates ordered steps with exact dollar amounts. Each step is backed by historical regime return data and shows the projected cost of inaction. Mark steps as done and the plan recalculates.
The regime transition model tracks how close each macro input is to its threshold. When a shift is likely, the engine shows what to do on day one of the new regime so you can position ahead of the move.
The transition model monitors the distance between each regime input and its scoring threshold. When multiple metrics approach their flip points simultaneously, the probability of a regime shift increases.
Applied retroactively to historical data since 2008, the model flagged 12 major regime transitions with an average lead time of 22 days before the shift confirmed. This is backtested, not a live prediction track record.
| Source | Series |
|---|---|
| FRED Federal Reserve Economic Data | WALCL, WTREGEN, RRPONTSYD, M2SL, DGS2, DGS10, BAMLH0A0HYM2, NFCI, UNRATE, DFF |
| Yahoo Finance Market Price Data | BTC-USD, SPY, QQQ, DX-Y.NYB, ^VIX, GLD, TLT |
All data refreshes daily. Macro series from FRED update on their official release schedule (typically weekly for balance sheet data, monthly for M2 and employment).
Track net liquidity, regime shifts, and 30+ macro indicators. Get regime-aligned action plans for your portfolio.