Daily Treasury Statement — Private Sector Impact

Leading indicator composite (7 indicators): WTI crude (level/momentum × fiscal vulnerability — dampened when fiscal flows are strong), SYF/COF 30+ day delinquency rate (leads NCO by 2-4 quarters), bank credit YoY growth (TOTLL), initial jobless claims 4-week MA YoY (ICSA), and loan officer tightening standards (DRTSCILM). HY OAS excluded from inputs — used as prediction target. Each threshold-based indicator standardized over selected baseline window. Multiplied by TDSP resilience factor. Fiscal impulse weight user-adjustable. Regime history shows composite vs HY OAS and VIX. Spread prediction tests whether composite predicts HY OAS change 63 days forward. Dislocation gap shows when leading indicators diverge from current spread levels.

Nominal: trailing 365-day net flows ÷ nominal GDP (quarterly BEA, interpolated). Real method 1: nominal % GDP minus trailing 12-month CPI-U — answers "is the injection outpacing inflation?". Real method 2: CPI-deflated net flows ÷ real GDP (chained 2017$) — the rigorous real fiscal impulse. Positive = private sector gaining real purchasing power. Negative = losing it.

Impact = gov spending − gov revenue (ex public debt issuances & redemptions). Positive = gov deficit = net injection into private sector. Figures in millions of USD.

Fiscal impulse = nominal rolling net flows (spending − revenue, ex-debt). Index data: Yahoo Finance. "Level + IORB adj." adds the weekly change in the Fed's deferred asset (H.4.1 RESPPLLOPNWW) as an off-balance-sheet injection — positive when the Fed is operating at a loss and not remitting to Treasury. Correlation coefficients use daily observations aligned by date. Forward returns are log returns over N trading days. Note: correlation ≠ causation. Fiscal impulse is one of many drivers of equity returns.

OAS = Option-Adjusted Spread over comparable Treasury. Higher = more credit risk premium demanded by market. Source: ICE BofA indices via FRED (BAMLH0A0HYM2). Dislocation signal: when leading indicators diverge from tight spreads, the market has not yet priced in deteriorating fundamentals.

Daily federal withholding tax deposits — a real-time proxy for payroll and employment. YoY change accelerating = labor market strengthening. Decelerating = early warning of stress, typically 2-4 months before credit metrics deteriorate. DTS only (2025+): like-for-like daily comparison using rolling 30-day sums — cleanest signal. FRED only (2006–2023): historical context via FRED WRMFSL weekly series. The two sources have different scopes (DTS includes FICA; FRED is income tax withholding only) and should be read separately.

WTI crude oil spot price ($/barrel). Supply shocks above ~$90/bbl historically precede credit stress with a 2-4 month lag, as energy costs crowd out debt service. Source: FRED DCOILWTICO.

Freight volumes are a real-time read on physical economic activity — distinct from financial flows and often leading GDP by 1-2 quarters. Rail carloads (ex-coal/grain) track industrial goods; intermodal tracks consumer/retail. Cass expenditures ÷ shipments is an implied freight price index — rising faster than volume signals tight capacity or fuel pass-through.

Carloads (SA, RAILFRTCARLOADSD11) excludes coal and grain — the AAR Freight Rail Index approach Warren Buffett uses as a proxy for broad industrial activity. Intermodal (RAILFRTINTERMODALD11) tracks consumer/retail goods and import flows.

Truck tonnage (TRUCKD11, ATA) and the BTS Freight Transportation Services Index (TSIFRGHT) — a composite across rail, truck, air, water, and pipeline.

Cass shipments (FRGSHPUSM649NCIS) = multi-modal volume proxy. Implied price = expenditures ÷ shipments ratio YoY. When implied price runs above volume, freight capacity is tight relative to demand — but this divergence does not itself destroy demand. Historically (2018, 2021-22) the subsequent volume collapse followed a withdrawal of fiscal flows, not high freight rates. Watch the DTS impulse, not the price spread, as the demand risk trigger.

Capacity utilization and industrial production cross-check the freight signals: rising freight with rising utilization confirms genuine expansion; rising freight with flat/falling utilization suggests pull-forward or mix shift rather than broad-based growth. The drilling IP index is the FRED equivalent of the Baker Hughes rig count — energy capex intentions expressed in realized activity.

Total capacity utilization (TCU) above ~80% historically signals pricing power and capex acceleration; below ~75% signals excess supply and margin pressure. Industrial production (INDPRO) is the broadest output composite across manufacturing, mining, and utilities.

Manufacturing IP (IPMAN), primary metals/steel (IPG331S), and electric power (IPG2211A2N). Steel leads construction and auto capex by 1-2 quarters. Power consumption is increasingly noisy due to data center demand but still confirms factory activity.

Industrial Production: Drilling Oil and Gas Wells (IPN213111S, index 2017=100). This is the Federal Reserve's monthly SA measure of drilling activity — closely tracks the weekly Baker Hughes rig count. Rising = energy companies committing capex, expecting prices to hold. Falling sharply = demand destruction signal for oilfield services and industrial supply chains.

Monthly data from SEC EDGAR 8-K filings. AXP (prime/affluent) vs SYF/COF (mass market/subprime) divergence reflects income distribution effects — lower-income cardholders feel energy and fiscal shocks first. Delinquency rates lead charge-offs by 2-4 quarters. Source: issuer monthly managed data releases.

Display-only context indicators. Both are lagging/coincident — they confirm stress already visible in delinquency data rather than predicting it. Useful for cycle positioning.

Source: Federal Reserve via FRED.

Tests whether the credit risk composite predicts forward equity returns across indices and sectors. Negative r = high composite predicts negative returns (risk-off consistent with credit stress). Sector divergence reveals which parts of the market are most sensitive to the composite's mechanisms.

Each dot = one trading day. x = leading composite score, y = forward equity return over selected window. Sector ETF data from Yahoo Finance via Netlify proxy. S&P 500 and Russell 2000 back to 2005; sector ETFs back to 2005 (XLF, XLY, XLE, XLK inception ~1998). Negative correlation is theoretically expected — credit stress composite should predict equity drawdowns, with consumer-facing sectors (XLY, XLF) more sensitive than defensive (XLK, XLV). Important caveat: full-history equity correlations are significantly influenced by the 2008-2009 GFC. Use the Ex-2008 toggle to assess robustness — without GFC, r values compress substantially, indicating the equity signal is strongest as a tail-risk indicator (composite >+1.5σ) rather than a routine tactical signal. The credit spread model (r=0.260, HY OAS) is the primary analytical output and shows genuine multi-cycle predictive content.

Sum of all government and central bank liabilities held by the private sector: privately held Treasuries, reserve balances, currency in circulation, and Fed reverse repo. By sectoral balances identity, this equals total private sector net financial savings created by the government sector. YoY change should track closely with the DTS fiscal impulse.

Sources: FRED FYGFDPUN minus FDHBFRBN (privately held Treasuries ex-Fed, $B), WRESBAL (reserve balances, $B), WCURCIR (currency in circulation, $B), WLRRAL (reverse repo H.4.1 weekly, $B). All weekly/monthly frequency. Total = sum of all four components. YoY change should reconcile with DTS-based fiscal impulse (differences reflect Fed balance sheet operations not captured in DTS spending data).

Daily Treasury Statement spending broken down by agency/category (post-2021). Shows which sectors of the economy are receiving accelerating or decelerating government flows — a real-time sector rotation signal visible before earnings reports or economic data releases.

Source: Daily Treasury Statement (DTS) via Treasury FiscalData API. Category breakdown available post-2021 only (TGA restructuring). Rolling sums smooth daily payment clustering. YoY acceleration = (current 90d sum) / (prior year 90d sum) - 1. Sector ETF correlation uses 90-day spending YoY vs 63-day forward ETF return.