Market Intelligence Deck

Understanding the Airbag (Gap Risk)

The pipeline computes this measure as |open - previous close| / (high - low). It is a simple but powerful way to estimate how much of the day’s realized move happened before continuous trading even began.

When this ratio is high, price discovery is happening in jumps rather than through orderly intraday matching. That often means displayed liquidity looked fine until it suddenly vanished, which is why the chart acts like an “airbag” or gap-risk gauge.

• Low values: most of the move is being discovered during the trading session.
• High values: the market is moving in discontinuous steps, a classic sign of fragile liquidity.
• Repeated spikes above the historical high percentile: conditions are unstable even if realized close-to-close volatility still looks moderate.

Understanding Plumbing Decomposition

This chart is intentionally more mechanical than abstract. It places the balance-sheet components that matter most for market liquidity on the same canvas: Fed total assets, reserve balances, and the two main drains on private-system cash, Reverse Repo and the Treasury General Account. The bold line is the derived net liquidity series.

That makes the panel much more actionable than a generic breadth-style indicator. When reserves are rising and the cash drains are easing, risk assets usually face a friendlier background. When TGA rebuilding or RRP absorption offsets central-bank support, the net line tells you that the headline policy narrative may be overstating actual liquidity reaching markets.

• Net liquidity rising: the plumbing backdrop is improving even if rates remain restrictive.
• TGA or RRP moving sharply lower on the chart: those are liquidity drains intensifying.
• Fed assets stable but net liquidity weakening: policy optics may look unchanged while usable market liquidity is still deteriorating.

Understanding the Margin Debt Oscillator

The service layer computes two 12-month rates of change from FINRA data: one for margin debit balances and one for free credit cash accounts. The chart uses both series and highlights their spread as a simple leverage-versus-buffer monitor.

Margin debt growth by itself is not automatically bearish. The problem starts when leverage is rising faster than the cash cushion available to absorb volatility. That is when even modest drawdowns can create reflexive forced selling.

• Margin ROC above cash ROC: leverage is building faster than liquidity buffers.
• Both rising together: speculative activity is increasing, but the system still has more internal cash support.
• Margin falling and cash rising: deleveraging / repair phase.

Understanding the Refinancing Wall

The liquidity engine defines the current cost of debt as US 10Y yield + BBB OAS. It then compares that against a rolling average legacy rate over the configured refinancing lookback window. The difference is the refinancing-stress series.

This is a corporate balance-sheet stress test. It asks what happens when old debt issued in a cheaper regime has to be refinanced at today’s market rate.

• Positive values: rolling debt is becoming more expensive than the debt stock firms are carrying.
• Negative values: the current market is easier than the embedded legacy financing cost.
• Persistent positive spikes: pressure on buybacks, margins, weaker issuers, and default risk.

Understanding Refi Stress vs HY OAS

The grey shaded line is the engineered refinancing stress series (current cost of debt − rolling legacy cost). The purple line is HY OAS on the secondary axis. The point of the dual axis is to test whether bond markets are pricing the same rollover pressure that the refi-stress construction implies.

This is more decision-useful than plotting BBB and HY together (you can already read BBB level in the credit panel of the EVT & Risk tab and through the Refinancing Wall above). Pairing refi-stress with HY OAS isolates the unique question this tab should answer: is the funding wall already showing up in market pricing?

• Refi up, HY tight: the cost wall exists, but lenders are not yet demanding extra compensation. Often the slow-burn phase before equities admit it.
• Refi up, HY widening: credit is confirming the rollover stress. Earnings and default-cycle risk become more concrete.
• Refi down, HY tight: rollover headwind easing while lenders relax — the cleanest combination for risk assets.

Understanding the Drains-to-Stock Ratio

This metric divides the two main private-cash drains — Reverse Repo and the Treasury General Account — by Fed total assets, then converts to percent. Compared to the trillion-dollar levels in the Plumbing Decomposition chart, this ratio is scale-independent: you can read "how clogged are the pipes" without having to mentally normalize against the size of the balance sheet.

• Ratio rising: drains absorbing a bigger share of central-bank stock; usable market liquidity is being held back.
• Ratio falling: RRP runoff and/or TGA spend are releasing cash into the system.
• Ratio stable while Fed assets fall: QT may be bigger optics than impact if drains contract proportionally.

Understanding MOVE vs HY OAS

The amber line is the MOVE index, a measure of implied volatility on Treasury options. The purple line is HY OAS. Treasury volatility tends to lead credit spread moves because rates volatility directly raises the cost of dealer balance-sheet usage and re-prices the discount rate that all credit instruments use.

• MOVE up, HY still tight: the rates channel is signaling stress before credit confirms it. Watch for HY to follow.
• Both up together: stress is broad — funding pressure has reached the credit market.
• MOVE falling, HY widening: credit spread moves are likely idiosyncratic / sector-specific rather than rate-driven.

Understanding Hedge Fund Shadow Financing

This chart combines three borrowing channels — OFR hedge-fund repo financing, prime broker borrowing, and hedge-fund leveraged loans — and overlays the US 10Y yield as a simple tightening proxy on the secondary axis.

The key question is not just whether leverage is high, but whether it is being carried in an environment where funding and carry are becoming less forgiving. That combination often looks fine until volatility returns and deleveraging becomes abrupt.

• Borrowing rising while rates rise: leverage is building into tighter conditions.
• Borrowing stable / falling while rates rise: balance sheets may already be self-protecting.
• Borrowing high but rates easing: the setup is still levered, but the funding backdrop is less hostile.

Understanding the Global Proxy

The liquidity engine intentionally uses an inverted broad USD index as a lightweight global liquidity proxy. It is not trying to replicate every cross-border channel; it is capturing the broad reality that a stronger dollar tends to tighten global financial conditions, especially for external borrowers and emerging markets.

• Proxy rising: dollar weakness is easing conditions globally.
• Proxy falling: dollar strength is acting like a cross-border tightening force.
• Large down moves alongside rising EM stress: the global liquidity valve is closing.

Understanding Systemic Entropy

The engine standardizes rolling asset returns, builds a correlation matrix, extracts its eigenvalues, normalizes them into probabilities, and then computes Shannon entropy. In plain English, it asks how many independent “risk directions” the market currently has.

When entropy falls, more variance is being explained by fewer common factors. That often means the market is becoming more one-dimensional and more exposed to systemic flow shocks. Higher entropy suggests a more distributed structure.

• Entropy high/stable: risk is spread across more independent drivers.
• Entropy falling: the market is becoming more synchronized and systemically fragile.
• Sharp drops: macro regimes or stress events are starting to dominate everything at once.

Understanding Emerging Market Volatility

This panel plots the VXEEM index directly. Unlike the more engineered charts above, the value here is in the market price itself. Emerging markets are often the first place global liquidity stress becomes visible because of their external funding sensitivity and higher dependence on dollar conditions.

• VXEEM rising: external stress is building and global liquidity is likely tightening.
• VXEEM falling: external conditions are easing.
• VXEEM up while domestic US charts still look calm: a useful warning that the pressure may be starting offshore first.

Understanding the Panic Monitor

The frontend splits the VIX term structure into two curves: a medium-horizon spread and an ultra-short-horizon spread. Under normal conditions, volatility futures and longer-tenor implied volatility trade above spot volatility, which produces positive contango. In stress, the front of the curve becomes more expensive than the back, which produces inversion.

The red regime bands are not discretionary. They come from the engineered panic flag, which is triggered when the 9-day spread turns positive against spot, i.e. when very near-term protection becomes more expensive than the current VIX level.

• Positive spreads: calmer, more normal volatility carry conditions.
• Negative spreads / inversion: urgent demand for near-term protection.
• Repeated red bands: the market is moving from ordinary volatility into event-driven stress.

Understanding the Systemic Risk Monitor

This chart plots the one-month and three-month implied correlation series, with the option to overlay emerging-market volatility. Implied correlation asks a practical portfolio question: are stocks expected to move independently, or together as one macro block?

The critical insight is that a market can look diversified on paper while becoming highly correlated in practice. When implied correlation climbs, diversification benefits compress because index members are increasingly expected to move in lockstep.

• Low/stable correlation: more room for stock-picking and sector diversification.
• Correlation climbing toward 60%: systemic liquidation risk is increasing.
• Correlation high and VXEEM rising: a broader cross-asset stress regime may be forming.

Understanding the Tail Fragility Gauge

The ξ series comes straight from the generalized Pareto fit in the EVT engine. It is not a realized-volatility measure; it is a shape parameter for the extreme-loss distribution. That makes it one of the most structurally important variables on the entire tab.

The zones on the chart translate the math into a practical interpretation. Lower values imply a more well-behaved tail. Higher values imply increasingly heavy tails, where large losses become more probable and diversification behaves worse.

• Below ~0.20: tail behavior is relatively stable.
• 0.20 to 0.35: caution zone; the market is becoming more fragile.
• Above ~0.35: heavy-tail regime where crash risk can accelerate quickly.

Note on thresholds: the 0.20 / 0.35 cutoffs are conventional GPD interpretation bands from the EVT literature (ξ < 0 → bounded tail; 0 < ξ < 0.2 → light heavy-tail; ξ > 0.5 → infinite-variance regime). They are not derived from this dataset's own ξ distribution — they are external rules of thumb. Treat them as orienting bands, not as statistical p-value boundaries.

Understanding the Forecast Context Chart

This panel is a context check between recent realized returns and the model’s current forward-looking tail forecast. The histogram uses about one year of daily returns. The vertical lines mark the current one-day VaR and ES from the EVT model.

Why this matters: a tail forecast can look large or small in isolation, but it becomes more interpretable when you see where it sits relative to the distribution investors have actually experienced recently. If the VaR and ES lines sit deep in the left tail relative to last year’s returns, the model is saying the market’s current volatility/tail regime is more dangerous than ordinary recent history suggests.

• VaR/ES near the center of the histogram: current stress is modest relative to recent history.
• VaR/ES far into the left tail: today’s regime implies a much harsher downside than the average recent day.
• ES much farther left than VaR: once the loss threshold fails, the model expects a sharp deterioration in outcomes.

Understanding Stress Transmission

This panel replaces the old unconditional correlation matrix with a more decision-useful transmission chart. It standardizes EVT VaR, high-yield OAS, and OFR FSI onto the same z-score scale, so you can see whether risk-model stress is being confirmed by the credit market and the broader financial system.

That makes the comparison financially cleaner. Instead of asking whether raw levels happened to co-move over the full sample, the chart asks whether each series is currently elevated relative to its own history. When all three rise together, the regime is broadening from equity-volatility stress into a more systemic tightening episode.

• VaR up alone: stress is still mainly an equity-tail story.
• VaR + HY OAS up: credit is confirming that downside risk is becoming more fundamental.
• All three up together: market stress is widening into a genuine macro-financial transmission channel.

Understanding the Credit Confirmation Scatter

This scatter is designed as a confirmation check, not a generic factor playground. It asks whether the risk engine is rising in the same part of state-space where credit spreads are already widening and systemic stress is already elevated.

That is more valuable than a heatmap click-through because it directly tests whether the current regime looks like a genuine tightening episode. A high VaR reading with still-benign credit spreads is a different problem from a high VaR reading that sits deep inside a cluster of wide-spread, high-stress observations.

• Upward-sloping cloud: credit and modeled tail risk are reinforcing each other.
• Latest star above the cluster: the equity-risk model is running hot relative to credit.
• Latest star deep in the top-right with high stress color: the regime is broad, not isolated.

Understanding Equity Risk Premium vs Real Hurdle

The green line is the Shiller excess CAPE yield, which is a valuation yield measure rather than a market-cap ratio. The orange line is the forward real yield, a more investable proxy for the real discount rate than backward-looking CPI subtraction. The dotted term premium line helps users separate higher real yields driven by term compensation from higher real yields driven by tighter expected policy.

This framing is financially stronger because it places an equity valuation yield directly against a real fixed-income hurdle. When the excess CAPE yield is comfortably above forward real yields, valuation has more macro support. When the gap compresses, equities are offering less compensation for risk precisely as the real alternative improves.

• Excess CAPE yield above real yield: valuation has more breathing room.
• Gap compressing: multiple risk is rising.
• Real yield up and term premium up together: the hurdle is rising in a more hostile way for long-duration assets.

Understanding Liquidity vs Valuation

The x-axis shows the liquidity impulse/support signal. The y-axis shows Buffett Indicator as valuation. Each point is a month-end state, with the current point marked by a star.

• High valuation + weak liquidity: the market has less margin for error.
• High valuation + strong liquidity: expensive assets can still be supported, but dependence on liquidity is higher.
• Lower valuation + improving liquidity: the setup becomes more attractive if credit and breadth also confirm.

This chart deliberately avoids coloring by future returns, so it does not introduce look-ahead bias into the research UI.

Understanding Credit Transmission

The red line is SLOOS tightening, which measures how many banks are tightening commercial and industrial lending standards. The blue line is the broad NFCI conditions backdrop. Used together, they provide a better macro-financial transmission chart than generic factor correlations.

When SLOOS turns higher, the banking system is explicitly becoming less willing to extend credit. If the conditions index then tightens alongside it, the message is confirming: lending restraint is no longer just survey noise; it is spreading into market pricing and financing conditions.

• SLOOS up first: early credit tightening warning.
• Both rising: tightening is transmitting broadly.
• SLOOS easing while conditions remain tight: the market is still digesting prior restraint.

Understanding the ERP z-score

The green area is the Equity Risk Premium: excess CAPE yield − forward real yield in percentage points. It is the cleaner valuation gauge in this tab because it stays directly comparable to the macro discount-rate hurdle that drives every long-duration asset.

The dotted purple line is the 5-year rolling z-score of the same series. Levels matter, but where they sit in their own recent history matters more for sizing decisions. A z-score above +1 is "generously priced for the recent regime"; below −1 is "thin compensation given recent macro."

• ERP wide and z-score positive: equities are paying more compensation than the macro hurdle in recent history — supportive backdrop.
• ERP narrowing toward zero: the equity-yield cushion is being eroded by the rising real hurdle.
• z-score below −1: equities are being priced as if the future is much better than recent macro suggests — increases sensitivity to disappointing data.

This panel replaces the older Buffett-vs-S&P chart, which paired a slow-moving valuation indicator with the daily price line on a separate y-axis without true comparability.

Understanding the 10Y decomposition

The nominal US 10Y can be approximately decomposed into three pieces: forward real yield (what investors actually earn after inflation expectations), 10Y breakeven inflation (the market's implied inflation forecast), and term premium (extra compensation for holding long duration). The stacked area shows the contribution of each, and the black line is the actual US 10Y for fit comparison.

• Move driven by real yield: typically reflects expected policy and growth — most hostile to long-duration equities.
• Move driven by breakevens: inflation expectations are repricing — often reflects supply shocks or fiscal stimulus.
• Move driven by term premium: investors are demanding more compensation for duration risk — often reflects supply concerns, fiscal credibility, or volatility regime change.

The decomposition is not exact (the three pieces use slightly different underlying instruments), but the directional story is robust enough to make the macro reasoning explicit.

Understanding the Shadow Rate

The Atlanta Fed Wu-Xia shadow rate is a model-based estimate of what the Fed funds rate would be if it could go below zero. It uses the term structure of yields to back out the implicit policy stance during periods when conventional Fed funds is stuck at the zero lower bound. The dashed blue line is the 3-month T-bill as a market-based reference.

Why this matters: the post-GFC and post-COVID periods saw Fed funds pinned near zero while QE was actively easing financial conditions. A simple "rates are at 0" reading underestimates the dovish stance. A simple "rates are at 5.5%" reading overestimates how restrictive policy is once QT and balance-sheet runoff are added back. The shadow rate corrects both biases.

• Shadow much lower than T-bill: QE / forward guidance is doing extra easing the front-end rate cannot show.
• Shadow much higher than T-bill: QT / tightening of forward guidance is making policy more restrictive than the front rate suggests.
• Shadow ≈ T-bill: ordinary regime where the policy rate captures the full stance.

Understanding the Housing Spread

This panel compares the selected mortgage rate series — either 30Y mortgage or 15Y mortgage — against the US 10Y Treasury yield. The spread is the simple difference mortgage rate - 10Y Treasury yield. In other words, it measures how much extra compensation lenders demand above the benchmark risk-free rate to extend household credit.

That spread matters because mortgage rates are not determined by Treasuries alone. Bank balance-sheet pressure, securitization demand, regulatory constraints, and perceived consumer credit risk can all cause mortgage pricing to stay tight even when Treasury yields ease. That is why the spread acts as a useful real-economy financial-conditions gauge.

• Spread widening: lenders are tightening standards or demanding more compensation. Housing affordability worsens even if benchmark yields are stable.
• Spread narrowing: transmission is normalizing. Treasury relief is reaching the mortgage market more efficiently.
• High absolute mortgage rate + wide spread: the housing channel is under the most pressure, because both the risk-free base and the lending premium are restrictive.

Since housing is one of the fastest ways macro tightening reaches households, this chart is an excellent bridge between rates markets and the real economy.