Market Intelligence Deck
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Chart Explorer
Professional market analysis with dual-axis capabilities. Analyze lead-lag relationships by plotting two variables against the same timeline.
Dual-Axis Analysis
Compare up to 2 variables on the Primary (Right) axis and up to 2 variables on the Secondary (Left) axis.
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Regime Change (6M Corr) against S&P 500 (fixed)
Tracks the rolling 6-month correlation between your primary variable and the benchmark (S&P 500).
View detailed interpretation...
~0.0 → Independent / Uncorrelated
Negative → Hedge / Defensive / “Risk-Off” (moves opposite)
Data Browser
Loading Market Playbook...
Market Playbook
This tab answers four questions in order: (1) What is the current risk stance? (2) Which evidence block gives the strongest support? (3) Which warning deserves attention? (4) What contradiction should you investigate next? You get a quick snapshot, then confirmation, then context, then rotation signals.
Reading composite evidence across liquidity, credit, volatility, macro trend, valuation, participation, and positioning.
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Waiting for data.
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View detailed interpretation...
Understanding the Market Playbook
This tab converts existing Explorer signals into a simple regime read. It is not a trading signal. It is a checklist for deciding whether the market is supported by liquidity, credit, volatility, macro trend, valuation, participation, and positioning.
- Risk-on: most independent evidence blocks support risk-taking.
- Fragile risk-on: price or participation is supportive, but credit, volatility, rates, or valuation still warns against maximum exposure.
- Defensive: liquidity, credit, volatility, recession, or diversification evidence dominates the setup.
- Mixed: evidence is split, so position sizing and diversification matter more than directional conviction.
The useful part is the contradiction line: it tells you which specialist tab to inspect next before changing risk budget.
Risk-On / Risk-Off Matrix
A compact heatmap of independent risk channels. Latest values show current support/caution; 1M and 3M columns show whether the signal is improving or deteriorating.
View detailed interpretation...
How to read the confirmation matrix
Rows are normalized to a support/caution scale so very different market channels can be compared without pretending they use the same raw units. Green cells support risk-taking; red cells argue for caution. The percentile column shows where the latest normalized row sits relative to its own history.
- Broad green: liquidity, breadth, volatility, rates, and credit are confirming risk appetite.
- Mixed rows: risk can still work, but sizing should respect the disagreement.
- Green price rows with red credit or volatility rows: classic fragile risk-on setup.
- Red stock/bond correlation row: bonds are not providing the usual portfolio offset.
Risk Budget Map
A simple scoreboard of supportive vs cautionary evidence.
View detailed interpretation...
Understanding the Risk Budget Map
Each bar converts one macro or market theme into a comparable score from -1 to +1. Positive values are supportive of taking risk; negative values are cautionary. Most rows are based on where the latest reading sits versus its own history, so very different variables such as liquidity, credit spreads, volatility, rates, commodities, and positioning can be compared on the same scale.
Some inputs are inverted when lower values are healthier. For example, lower credit spreads, lower VIX, lower real yields, and lower stock/bond correlation improve the score, while stronger liquidity, breadth, and cyclical confirmation improve it directly.
Use it as a sizing guide rather than a forecast. Broad green confirmation supports a larger risk budget, broad red confirmation argues for defense, and a split map suggests patience, hedging, or smaller position sizes.
Cross-Asset Market Map
X-axis: 3M return (simple). Y-axis: 3-year z-score of price level (how stretched vs own history, not raw level). Bubble size: 63d realized volatility.
View detailed interpretation...
Understanding the Cross-Asset Market Map
The x-axis is the simple 3-month return in percent. The y-axis is the 3-year z-score of price level, i.e. how stretched the asset sits relative to its own three-year history — it is not a raw price or a return. A z-score of 0 is "average," +2 is two standard deviations above its own three-year mean, −2 is two below. Larger bubbles indicate higher 63-day realized volatility, and the legend separates equities, sectors, factors, fixed income, commodities, FX, crypto, and themes.
- Upper-right: strong and extended. Momentum is working, but late-entry risk rises.
- Lower-right: improving from a depressed base. This is where recoveries often start.
- Upper-left: stretched but losing momentum. Watch for failed leadership.
- Lower-left: weak and still below normal. Avoid assuming cheap means timely.
Sector / Factor Leadership Board
Ranks the strongest and weakest tradable groups by 3M return.
View detailed interpretation...
Understanding the Leadership Board
This board is designed to make the Playbook more actionable without turning it into a stock-picking screen. It ranks broad sectors, factors, themes, commodities, currencies, and fixed-income proxies by 3-month performance, then adds drawdown, volatility, correlation, and percentile context.
- Leaders with low drawdown and broad confirmation: healthier leadership.
- Leaders with high volatility and high extension: momentum exists, but sizing risk is higher.
- Laggards improving in the Cross-Asset Map: possible rotation candidates.
Regime Timeline
Thin bands show which regime warnings appeared first.
View detailed interpretation...
Understanding the Regime Timeline
The timeline shows the same regime evidence through time, sampled around month-end. Each row is simplified into green, neutral, or red: green means the signal was supportive, red means cautionary, and neutral means the reading was not strong enough to dominate.
This helps separate isolated warnings from broad regime shifts. Liquidity and credit rows use the normalized risk-budget scores, while binary rows such as recession or VIX panic turn red only when the warning regime is active. The stock/bond correlation row turns red when diversification is weakening and green when bonds are behaving more defensively.
- Liquidity or yield-curve rows turning red first: macro/financial conditions may be leading the warning.
- Credit and VIX rows turning red together: market stress is becoming more confirmatory.
- Stock/bond correlation turning red: normal diversification assumptions are weakening.
Loading Liquidity Dynamics...
Liquidity Control Center
This tab monitors liquidity, funding conditions, and cross-asset fragility. It tracks whether central banks are injecting fuel, whether market plumbing is clogged, and whether the cost of money is becoming a funding wall.
Analyzing the current liquidity regime.
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Liquidity Impulse (3M)
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Liquidity impulse.
Shock Signal (1M)
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Sudden injections or drains.
Gap Risk (Airbag)
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Overnight liquidity voids.
Refi Stress
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Cost of new debt vs. old.
Macro Engine (The Driver)
Liquidity Impulse & Shock
Is system liquidity becoming more supportive or more restrictive?
View detailed interpretation...
Understanding Liquidity Impulse & Shock
The engine first builds Net Liquidity as Fed total assets - Treasury General Account - Reverse Repo, with the Fed balance sheet lagged appropriately for daily data. The chart does not plot that level directly. Instead it plots the 3-month log change of net liquidity as bars and the 1-month log change as the line.
That distinction matters. The bars are the medium-term flow trend; the line is the short-term jolt. A market can still have plenty of absolute liquidity while the flow is deteriorating, and assets tend to care a lot about the direction of the change.
- Green bars: net liquidity is higher than about 63 trading days ago.
- Red bars: net liquidity is lower than about 63 trading days ago.
- Shock diverging from impulse: a short-term injection or drain may be arriving before the broader 3-month trend has turned.
Read it as a structural wind map, not a one-chart market timing system. Liquidity can dominate for long stretches, but earnings, credit stress, and recession risk can still override it.
Reserves Strain Gauge
Net Liquidity scaled by S&P 500 Price.
View detailed interpretation...
Understanding the Reserves Strain Gauge
This metric is intentionally simple: it takes the engineered net liquidity level and divides it by the S&P 500 price. In other words, it asks how much system liquidity exists per unit of index price.
That makes the chart a liquidity-scaled valuation gauge. It does not claim to be fair value; it simply checks whether asset prices are rising faster than the liquidity pool supporting them.
- Ratio rising: liquidity support is improving relative to the market level.
- Ratio falling while price rises: valuation is becoming more dependent on optimism, concentration, or leverage than on system liquidity.
- Sharp downward breaks: a sign that the market is vulnerable to more air-pocket behavior if a shock hits.
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Market Plumbing (The Pipes)
The "Airbag" (Gap Risk)
How often does the market open far away from the prior close?
View detailed interpretation...
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.
Plumbing Decomposition
Fed assets, reserves, RRP, TGA, and the derived net-liquidity pulse in one chart.
View detailed interpretation...
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.
Margin Debt Oscillator
12M rate of change: Margin Debt vs Free Cash (FINRA). Divergence = forced liquidation risk.
margin debt 12M ROC - free cash 12M ROC. When leverage is accelerating and cash buffers are not, the system becomes easier to knock off balance.View detailed interpretation...
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.
Funding Liquidity (The Cost)
The "Refinancing Wall"
Current Cost of Debt vs. Legacy Rates.
current cost of debt - legacy cost of debt. When it stays positive, borrowers rolling old paper face an earnings and cash-flow penalty even if the broad market still looks fine.View detailed interpretation...
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.
Refi Stress vs HY OAS
Engineered refi stress (left) against High-Yield OAS (right) — does credit confirm the rollover wall?
current − legacy debt cost gap) and HY OAS rise together, both the cost-of-rolling and the lenders’ compensation are tightening — credit is confirming the funding wall.View detailed interpretation...
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.
Drains-to-Stock Ratio
(Reverse Repo + TGA) as a percentage of Fed total assets — scale-independent plumbing pressure.
View detailed interpretation...
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.
MOVE Index vs HY OAS
Treasury implied volatility (left) against High-Yield OAS (right) — bond vol typically leads credit.
View detailed interpretation...
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.
Hedge Fund Shadow Financing
Stacked borrowing channels (levels) vs a tightening proxy (rate line).
View detailed interpretation...
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.
Global Context (The Valve)
Global Proxy (Inverted USD)
A weak Dollar acts as global liquidity injection.
1 / broad USD index. When it rises, the dollar is weakening and global liquidity conditions usually ease; when it falls, dollar tightness is acting like a drain.View detailed interpretation...
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.
Systemic Entropy
Measure of correlation breakdown/chaos.
View detailed interpretation...
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.
Emerging Market Volatility (VXEEM)
Rising VXEEM signals tightening USD liquidity and stress in emerging markets.
View detailed interpretation...
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.
Liquidity Trading Guide
1. The Macro Tide
Net Liquidity is the baseline fuel. We watch the Impulse (3M change) rather than the total level.
- Green Impulse: Fed is effectively easing or Treasury is spending into the system. Dips have more structural support.
- Red Impulse: liquidity is being withdrawn. Valuation and leverage become more vulnerable.
2. Market Plumbing
Even with high liquidity, the market can break if the pipes are clogged.
- Gap Risk: tells you whether liquidity disappears when the market is stressed.
- Plumbing Decomposition: tells you whether usable market liquidity is actually improving once Fed assets, reserves, TGA, and RRP are netted together.
3. Funding Costs
The cost of leverage determines whether available liquidity can actually be used.
- Refi Stress: aggregate rollover pressure on corporate balance sheets.
- Credit Spreads: bond-market confirmation of whether lenders still want to fund risk.
Loading EVT & Risk Structure...
Risk Control Center
Confidence detail: --
This tab monitors tail risk, volatility structure, credit stress, recession pressure, and stock/bond diversification. You get model health first, then the anatomy of fear, then stress confirmation.
Initializing tail-risk regime diagnostics.
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99.9% VaR (1-Day)
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Capital at risk tomorrow.
ES-VaR Gap
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Added loss if VaR fails.
Tail Fragility (ξ)
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Market Physics Monitor
Backtest Status
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Rolling 1Y Accuracy
Risk Radars: The Anatomy of Fear
These three radars show what kind of stress is building: panic in volatility markets, systemic correlation spikes, and recessionary tail risk from the real economy.
The Panic Monitor (VIX Term Structure)
Positive = Contango (calm), Negative = Inversion (panic). Red background bands highlight active panic regimes.
VIX3M - VIX and VIX9D - VIX. When short-dated vol moves above spot vol, the curve inverts and the panic regime flag turns on.View detailed interpretation...
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.
The Systemic Risk Monitor (Implied Correlation)
Rising correlation means diversification is failing. Watch the 60% line for systemic liquidation risk.
View detailed interpretation...
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.
VVIX vs VIX (Vol of Vol)
VVIX prices uncertainty in the VIX itself. When VVIX stays elevated after VIX mean-reverts, the market is still pricing tail-event risk under the surface.
View detailed interpretation...
Understanding VVIX vs VIX
VIX measures expected near-term equity volatility; VVIX measures expected volatility of VIX itself. They normally move together, because vol-of-vol is fed by vol.
The interesting cases are the disagreements. Persistently elevated VVIX with a low VIX is a known precursor to vol shocks: investors are paying up for exposure to changes in volatility even when realised vol is benign. The opposite — calm VVIX while VIX rises — typically reflects an orderly drift higher rather than a discontinuous repricing.
- Both up together: ordinary vol regime; spot fear and forward fear are aligned.
- VVIX up, VIX low: dealers and speculators are positioning for vol-of-vol expansion. Often precedes a VIX spike.
- VVIX falling faster than VIX: the recent vol shock is being digested; tail demand is unwinding.
MOVE / VIX Ratio
Treasury volatility relative to equity volatility — when bond vol leads equity vol, the source of stress is rates.
View detailed interpretation...
Understanding MOVE / VIX
The MOVE index is the Treasury-options analogue of VIX. Dividing it by VIX gives a unit-free ratio of rates volatility per unit of equity volatility. The chart adds a cross-asset confirmation that the EVT engine alone cannot provide: VaR is purely equity-tail; MOVE/VIX tells you whether the rates market is the actual source of the stress.
- Ratio rising: rates uncertainty is outpacing equity uncertainty. Often shows up before duration-sensitive sectors and credit react.
- Ratio falling: equity vol is dominating the cross-asset picture. The shock is more likely earnings/positioning than rate-policy.
- Ratio stable but high: a rates-led regime that has stabilised — markets have priced the new policy stance.
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If this report is helping you with your analysis, please consider supporting the project so we can keep it publicly accessible and free for everyone, as maintaining everything on cloud servers incurs ongoing costs.
VaR Breach Monitor
Are realized tail losses exceeding the forecast boundary?
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Understanding the VaR Breach Monitor
The filled area is the actual daily S&P return series. The model overlays the negative of the EVT VaR and the negative of the historical-simulation VaR so both appear as left-tail loss thresholds on the same chart. A breach occurs when the realized return is worse than the VaR estimate for that day.
In the EVT engine, returns are modeled through a GARCH volatility step plus a peaks-over-threshold generalized Pareto tail fit. That means the chart is not just a rolling quantile; it is trying to model how the extreme left tail behaves in different volatility regimes.
- Few isolated breaches: expected in any probabilistic model.
- Clustered breaches: the tail model is being outrun by a new stress regime.
- EVT line holding better than HS line: the tail-sensitive model is adapting better than a simple rolling historical window.
Expected Shortfall Gap (ES - VaR)
Measures how much worse expected tail losses are after the VaR threshold fails.
|ES| - |VaR|. It measures how much worse the average tail loss becomes once the VaR threshold has already failed.View detailed interpretation...
Understanding the Expected Shortfall Gap
VaR answers “how bad could a one-day move get at this confidence level?” Expected Shortfall answers “if that threshold fails, how bad are the tail losses on average?” The explorer derives this chart directly from the EVT outputs as the absolute gap between Expected Shortfall and Value-at-Risk.
That makes the panel a practical proxy for tail severity beyond the initial breach. A narrow gap means the model expects losses just beyond VaR to remain relatively contained. A wide gap means that once the boundary breaks, the left tail becomes much more punishing.
- Gap widening: the market is becoming less forgiving if a selloff escapes the normal risk boundary.
- Gap narrowing: tail severity is normalizing even if ordinary VaR remains elevated.
- Wide gap with rising breach count: the most dangerous combination, because the model is both failing more often and implying deeper post-breach losses.
Tail Fragility Gauge (ξ)
Stable (<0.20) vs Fragile (>0.35) zones.
View detailed interpretation...
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.
Recent Returns vs Current Risk Forecast
Histogram shows last ~1y realized returns. VaR reflects today’s volatility regime.
View detailed interpretation...
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.
Technical Analysis & Validation
Detailed breakdown of rolling one-year validation and cross-market stress confirmation.
Stress Transmission
Standardized view of EVT VaR, high-yield spreads, and OFR systemic stress.
View detailed interpretation...
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.
Credit Confirmation Scatter
High-yield spreads vs EVT VaR, colored by OFR systemic stress.
View detailed interpretation...
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.
Rolling 1Y Validation
Rolling 1Y breach validation aligned with the headline traffic-light logic.
View detailed interpretation...
Understanding Rolling 1Y Validation
The EVT pipeline does more than produce VaR. It also backtests the model over a rolling 252-day window and compares the number of observed breaches against the expected number implied by the effective confidence level. The table puts EVT and historical VaR on the same footing so you can see which engine is doing the better job.
Because the EVT engine can adapt confidence when history is limited, the target failure rate is not hard-coded mechanically; it respects the effective alpha used by the model. That makes the validation more honest than simply assuming a fixed textbook threshold in every regime.
- Actual failures near target: model calibration is behaving as expected.
- Too many failures: the model is underestimating risk.
- Far too few failures: the model may be overly conservative and less capital-efficient.
Market Validation & Blind Spots
Alternative signals to cross-reference with the primary risk model.
Recession Watch (Tail Risk)
Hamilton Recession Index vs Sahm Rule. Sahm Rule above 0.50 = recession trigger.
View detailed interpretation...
Understanding the Recession Watch
This panel combines two recession indicators with very different economic foundations. The chart plots the Sahm Rule and the Hamilton Recession Index, both displayed in percent terms in the frontend. The Sahm Rule is a labor-market deterioration trigger, while the Hamilton index measures how much GDP behavior resembles recessionary regimes.
Together they create a sequencing tool. The Hamilton series often acts like an earlier growth-sensitive warning. The Sahm Rule is usually later but cleaner, because it requires labor-market damage to become visible.
- Hamilton rising first: macro growth is weakening, but the labor market has not fully rolled over yet.
- Sahm above 0.50: the chart enters its formal recession-warning zone.
- Both elevated together: recession risk is no longer just a tail-risk scenario; it is becoming a macro base case.
Financial Stress Decomposition
Stacked sub-components (co-movement) with the overall stress index as a line.
View detailed interpretation...
Understanding Financial Stress Decomposition
This chart takes the OFR stress index apart. The stack shows the contribution of the key sub-components, while the top line shows the aggregate OFR Financial Stress Index. That helps distinguish between isolated noise and broad-based systemic pressure.
- Total line rising with a broader stack: stress is becoming systemic across multiple channels.
- Only one component driving: the problem may still be localized.
- Total line mean-reverting toward zero: stress is normalizing back toward the “ordinary conditions” baseline.
Stress Heatmap (Regional)
Trailing 36 month-end snapshots normalized by each region's own history to separate coordinated contagion from local stress.
View detailed interpretation...
Understanding the Regional Stress Heatmap
The heatmap compares regional OFR-style systemic stress across the United States, other advanced economies, and emerging markets, but it now standardizes each row against that region’s own history. That avoids the chart being dominated by a few old crisis spikes and makes the color intensity comparable across regions.
Because each row is standardized against its own history, the chart is better at showing whether multiple regions are heating up together versus just one region remaining idiosyncratically stressed.
- One row heating up: regional shock more likely.
- Multiple rows heating together: stress is globalizing.
- Emerging markets warming first: external financing and dollar sensitivity may be leading the warning.
Liquidity Airbag
Liquidity shocks during volatile regimes.
ΔLiquidity × VIX, and EVT VaR.View detailed interpretation...
Understanding the Liquidity Airbag
This panel combines the risk tab with the liquidity engine. The liquidity-shock proxy is engineered as net_liquidity_diff * VIX, so it becomes larger when liquidity is changing sharply during already-volatile conditions. The third axis adds the current EVT VaR so you can compare market-implied crash risk against liquidity support.
- Liquidity down, shock proxy up, VaR up: the “airbag” is failing right when risk is worsening.
- VaR high but liquidity stabilizing: the market may still be risky, but the plumbing is no longer deteriorating.
- Shock proxy easing: forced moves may start to lose intensity.
Complacency Gauge
Realized tail risk vs. Implied crash insurance.
View detailed interpretation...
Understanding the Complacency Gauge
The chart pairs the EVT tail index with SKEW. One is model-based and grounded in realized extreme-return behavior; the other is option-market pricing for tail insurance. Put together, they create a powerful disagreement signal.
- SKEW high, ξ low: the market is paying up for protection against a crash the realized tail model does not yet see.
- Both rising: realized and implied tail risk are confirming each other.
- ξ high, SKEW calm: options pricing may be under-reacting to deteriorating tail structure.
Stock–Bond Correlation Regime
When diversification stops working.
View detailed interpretation...
Understanding the Stock–Bond Correlation Regime
Traditional multi-asset portfolios rely on stocks and long bonds offsetting each other during risk-off episodes. This chart tests whether that assumption still holds by plotting the engineered 6-month stock–bond correlation.
- Negative correlation: traditional diversification is working.
- Correlation near zero: diversification help is fading.
- Positive correlation: “nowhere to hide” regime where stocks and bonds can fall together.
Equity-Credit Divergence
Equities against high-yield and BBB credit stress.
View detailed interpretation...
Understanding the Equity-Credit Divergence
The equity side of the chart uses the engineered S&P 500 3-year z-score, which measures how stretched the index is relative to its own longer history. The credit side uses high-yield OAS and BBB OAS, so you can distinguish lower-quality refinancing stress from investment-grade spread confirmation.
- Equities rich + spreads tight: risk-on conditions are broadly confirmed.
- Equities rich + spreads widening: credit is warning that the equity market may be overconfident.
- Equities cheap + spreads blowing out: stress is already explicit across both asset classes.
This chart deserves respect because credit often turns before equities do when financing conditions deteriorate.
This Risk tab turns rare losses into a measurable system. Instead of asking only how volatile the market has been lately, it asks how dangerous the extreme left tail looks right now, whether the model has been honest in live backtests, and which external market channels are confirming or contradicting that risk message.
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Macroeconomic Cycle
This tab monitors the macro cycle, valuation hurdle, credit transmission, housing-rate pressure, and yield-curve regime. It helps separate rallies supported by fundamentals from rallies fighting liquidity, credit, or valuation gravity.
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The Economic Cycle
Visualizing the economy's position by plotting the Yield Curve Slope against the Inflation Gap with a cadence-aware path that respects macro update frequency.
View detailed interpretation...
Understanding the Economic Cycle Map
This chart plots two engineered macro features from the daily feature set. The x-axis is the yield curve slope, defined as US 10Y yield - US 2Y yield. The y-axis is the inflation gap, defined as CPI YoY - 3%. In the chart both are multiplied by 100, so they are displayed in percentage terms. The red star marks the current point, while the path is sampled weekly and on macro update dates so the visual does not pretend that forward-filled monthly inflation is a true daily signal.
Because the x-axis is the slope, moving left means the curve is flatter or more inverted, which usually reflects tighter policy or slower growth expectations. Because the y-axis is the inflation gap, moving up means inflation is running above the 3% reference threshold used by the model. The four quadrants therefore provide a compact state map of growth/inflation conditions.
- Bottom-right: positive slope and sub-threshold inflation. This is the cleanest “growth / disinflation” backdrop.
- Top-right: positive slope but inflation still hot. The economy is running strong, but overheating risk is present.
- Top-left: inverted or flat curve with high inflation. That is the most uncomfortable combination because policy may still be restrictive into weakening growth.
- Bottom-left: inverted curve and soft inflation. That is the classic recession / late-tightening zone.
The path is as important as the location. A move from top-right toward top-left is very different from a move from bottom-left toward bottom-right, even if both pass near the same coordinates.
State vs. momentum playbook
Use the quadrant as the state and the regime chart below as the momentum driver. The same quadrant can lead to very different outcomes depending on whether the curve is steepening because the front end is collapsing or because the long end is repricing inflation risk.
- Growth phase + bullish steepening: early-cycle recovery. Easier front-end policy usually supports equities and credit.
- Growth phase + bearish steepening: reflation or fiscal-dominance risk. Favor real assets and be cautious with long duration.
- Growth phase + bearish flattening: pre-emptive cooling. The Fed is leaning against strength, so carry matters more than beta.
- Overheating + bearish flattening: late-cycle peak. Policy is actively trying to slow demand, so defense matters more than upside chase.
- Overheating + bearish steepening: inflation panic. Rising long-end term premium is hostile for both stocks and bonds.
- Stagflation risk + bullish steepening: breaking point. The front end is finally giving way, often because recession stress is forcing a policy pivot.
- Recessionary + bullish flattening: deflationary bust. Long-duration bonds tend to be the cleanest safe haven.
- Recessionary + bullish steepening: liquidity rescue. This is often the phase where risk assets stop falling before the data turn.
Analytical rule: never read the quadrant in isolation. Always ask what is mathematically driving the move in the yield curve beneath it.
Yield Curve Shift Regimes (Time Series)
Visualizing the 3-month momentum of the yield curve. Plotting the 10Y-2Y spread, colored by the prevailing macroeconomic fixed income regime.
View detailed interpretation...
Understanding Yield Curve Shift Regimes
This chart uses the regime engine in app/services/explorer/drivers.py. First it computes the current spread as US10Y - US2Y. Then it measures the 3-month change in the 2-year yield, the 10-year yield, and the spread itself over roughly 63 trading days. A small-change band of 10 basis points is treated as neutral.
The regime names are not cosmetic. They are mechanically assigned from the relative moves of the front end and back end:
- Bearish flattening: the spread is shrinking and the 2Y is rising faster than the 10Y. That is the classic “Fed is tightening” message.
- Bullish flattening: the spread is shrinking because the 10Y is falling faster than the 2Y. That often reflects flight-to-safety demand or recession pricing.
- Bullish steepening: the spread is widening because the 2Y is falling faster than the 10Y. This is the classic easing / recession-recovery signal.
- Bearish steepening: the spread is widening because the 10Y is rising faster than the 2Y. That usually points to higher term premium, inflation concern, or fiscal pressure.
This is why the chart belongs under the cycle map above: the quadrant tells you the current macro state, while this regime chart tells you the bond-market momentum driver pushing the economy toward the next state.
Quick regime cheat sheet
- Bearish flattening: short rates rise faster than long rates. Usually a tightening phase; keep duration disciplined.
- Bullish steepening: short rates fall faster than long rates. Usually an easing or recession-recovery phase; duration and risk assets both gain breathing room.
- Bullish flattening: long rates fall faster than short rates. Usually a flight-to-safety move; long duration benefits most.
- Bearish steepening: long rates rise faster than short rates. Usually inflation, supply, or term-premium stress; long duration is the cleanest loser.
- Neutral / stable: the spread changed less than about 10 bps over the lookback. Carry matters more than directional curve bets.
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Valuation & Credit Conditions
Focusing on the variables that most directly shape discount rates, lending transmission, and the equity pricing backdrop.
Equity Risk Premium vs Real Hurdle
Shiller excess CAPE yield against forward real yields, with term premium as a regime overlay.
The most fragile setup is when the equity yield cushion shrinks while the real hurdle rate moves higher.
View detailed interpretation...
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.
Liquidity vs Valuation Regime
Liquidity support against the market valuation backdrop.
View detailed interpretation...
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.
Credit Transmission
Bank lending standards against broad financial conditions.
Tightening standards often reach the real economy before the equity tape fully admits it.
View detailed interpretation...
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.
Equity Risk Premium z-score (5y)
ERP = excess CAPE yield − forward real yield (left). Right axis shows the 5-year rolling z-score.
View detailed interpretation...
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.
Nominal 10Y Decomposition
Stacked area: forward real yield + 10Y breakeven inflation + 10Y term premium. Black line: actual US 10Y yield.
View detailed interpretation...
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.
Wu-Xia Shadow Rate vs 3M T-bill
Shadow funds rate (purple) is the only honest measure of policy stance during ZLB / QT periods. Right axis: shadow − T-bill gap.
View detailed interpretation...
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.
The Housing Spread
Tracking mortgage rates alongside the 10Y Treasury yield.
A wider spread signals banking stress as lenders pull back on credit.
View detailed interpretation...
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.
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The Sentiment Disconnect
This tab monitors the gap between what investors feel and what the market is doing. It compares sentiment, institutional confidence, breadth, risk appetite, volatility, and seasonal behavior to identify when psychology diverges from price.
1. Consumer Sentiment vs Equity Prices
Consumer Sentiment (Left) vs. S&P 500 Price (Right).
View detailed interpretation...
Understanding Consumer Sentiment vs Equity Prices
This chart is intentionally simple: it places the University of Michigan consumer sentiment index next to the S&P 500 price level. It does not transform either series into returns or z-scores. The point is to compare the direction of public mood with the direction of the equity benchmark.
That matters because household sentiment often captures the real-economy experience of inflation, labor-market stress, and financial pressure, while the S&P can be driven by a smaller set of factors such as earnings concentration, mega-cap leadership, or liquidity expectations. When those two stories diverge for long enough, the market is telling you something unusual about the source of the rally or selloff.
- Price up, sentiment flat/down: classic “soft public mood, strong market” divergence. The rally may be narrower and more vulnerable than the index suggests.
- Price down, sentiment stabilizing: fear may already be reflected in markets before households fully recover.
- Both rising or both falling: macro and market narratives are aligned, so the signal is less contrarian.
This is best used as a context chart. It highlights disconnects that you can then validate with breadth, risk appetite, and volatility structure below.
2. The "Wall of Worry" (Expectations)
VIX Curve Trend (VIX6M - VIX3M) vs. Global Policy Uncertainty.
View detailed interpretation...
Understanding the Wall of Worry
The purple series is the engineered VIX curve trend, defined in the composites engine as VIX6M - VIX3M. A rising value means medium-term implied volatility is becoming more expensive relative to nearer-dated volatility. The grey series is global policy uncertainty, which acts as a macro catalyst proxy.
This is useful because investors often hedge political, fiscal, geopolitical, or policy shocks first in options markets. If the volatility curve starts steepening upward before spot volatility really explodes, it can mean traders are paying for forward protection even while the near-term tape still looks calm.
- VIX curve trend up + policy uncertainty up: expectations and macro catalyst risk are reinforcing each other.
- VIX curve trend up while policy uncertainty is quiet: the options market may be seeing a risk that macro headlines have not fully explained yet.
- Both falling: the market is climbing the wall of worry more comfortably and forward hedging demand is easing.
Because the curve uses relative option pricing, it is often better at detecting latent concern than looking at the VIX level alone.
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2b. Institutional Cognitive Dissonance
Confidence in valuation (line) vs perceived crash probability (line).
View detailed interpretation...
Understanding Institutional Cognitive Dissonance
This chart overlays two institutional survey-style measures from the Yale data series: confidence in valuation and perceived crash probability. They are plotted as levels, because the interesting information is in the coexistence of the two attitudes rather than in a transformed spread.
If institutions say valuations are reasonable while simultaneously raising their expected crash probability, it means portfolios may still be invested even as tail-risk awareness rises. That often happens late in cycles when managers feel forced to stay exposed but are becoming less comfortable with the underlying setup.
- High confidence + high crash probability: classic dissonance regime. Positioning can remain risk-on, but the market becomes more sensitive to shocks.
- High confidence + low crash probability: cleaner institutional endorsement of the tape.
- Low confidence + high crash probability: already defensive psychology; risk-off conditions are more explicit.
Use this chart as a behavioral cross-check on the explicit volatility charts. Sometimes institutions verbalize concern before broad volatility measures fully catch up.
3. The "Engine" of the Market (Participation)
Breadth Ratio (Line) vs. S&P 500 (Right).
View detailed interpretation...
Understanding the Participation Engine
The breadth ratio comes from the composite engine and is defined as RSP / SP500, where RSP is the equal-weight S&P 500 ETF and SP500 is the cap-weight market proxy. When the ratio rises, the average stock is doing better relative to the cap-weighted index. When it falls, the index is being supported more by its largest names.
That makes this chart a very practical leadership monitor. A broad bull move normally requires many stocks to participate. A falling breadth ratio during an index rally means participation is narrowing, which does not automatically end the trend but usually makes it more fragile.
- Breadth ratio up: healthier participation and better internals.
- Breadth ratio down while price rises: concentration risk is building.
- Breadth ratio up while price stabilizes: internal repair may be happening beneath the surface.
This chart is one of the best companions to the sentiment and passive-flow charts, because it reveals whether the market’s emotional tone is being backed by actual participation.
5. Individual vs Institutional Confidence (Yale)
Yale ICF survey: individual-investor confidence vs institutional-investor confidence, with the gap as bars (right axis).
View detailed interpretation...
Understanding the Confidence Divergence
This chart pairs the two Yale International Center for Finance confidence indices: individual-investor confidence in amber and institutional-investor confidence in blue. The bar series at the bottom shows the gap (Individual − Institutional). They are plotted as raw index levels rather than transforms because the levels carry survey meaning.
Why this is true behavioral alpha: conventional sentiment proxies (VIX, SKEW) come from option pricing — they belong on the Risk tab, not here. The Yale ICF surveys actually ask different cohorts whether they believe the market is reasonably valued and likely to be higher in 6 months. When the two cohorts diverge, you are seeing positioning conflict that price-based proxies miss.
- Individuals up, institutions down: classic late-cycle distribution risk. The crowd is providing the bid.
- Institutions up, individuals down: contrarian setup more typical of recovery phases.
- Both rising: broad endorsement; momentum can persist longer.
- Both falling: capitulation signal candidate, especially when paired with widening credit spreads on the Liquidity tab.
6. AAII Payoff Scatter
X: AAII Bull − Bear spread (% of survey respondents). Y: S&P 500 forward 21-trading-day return. Colour scales the realised forward return.
View detailed interpretation...
Understanding the AAII Payoff Scatter
The x-axis is the AAII bull − bear spread (percent of bullish respondents minus percent bearish, displayed as a percentage). The y-axis is the realised S&P 500 forward 21-trading-day return, computed as (price[t+21] / price[t]) − 1. Each dot is one historical date; colour also encodes the realised forward return so clusters are easy to read.
This replaces the previous VIX-panic scatter because AAII is a genuinely behavioural input (a survey of households' directional sentiment) rather than an option-implied measure that already lives on the Risk tab. The shape of the cloud often shows the contrarian property of crowd sentiment more clearly than VIX shows the "panic pays" property.
- Far right (extreme bullish): historically associated with thinner forward returns. Crowded longs.
- Far left (extreme bearish): historically associated with stronger forward returns. Capitulation setups.
- Centre cluster: ordinary regimes; the signal is weaker, and other factors dominate.
- Last point (red star): ~21 trading days behind today, because the forward return window for "today" is not yet realised.
This chart is probabilistic, not deterministic. It shows the historical distribution of forward returns conditioned on sentiment regime, not a forecast for any individual date.
Market Seasonality
Analyze historical monthly returns to identify seasonal patterns.
View detailed interpretation...
Understanding the Seasonality Heatmaps
The seasonality module works from the selected monthly dataset column. The frontend steps through the time series, detects each month change, and computes a simple monthly return as (current / previous) - 1. That produces one monthly return value for each year-month pair. Those values populate the left heatmap, while the right heatmap shows the average return for each calendar month over the selected range.
Because the color scale is centered around zero, green months are positive on average and red months are negative on average. The left panel is useful for seeing consistency or instability through time; the right panel compresses that information into the typical seasonal pattern.
- Consistent color across many years: stronger seasonality signal.
- Average looks strong but yearly panel is mixed: the mean may be driven by a few outliers rather than a stable calendar effect.
- Changing the variable: lets you test whether the pattern is specific to one asset or shared across related series.
Seasonality is best treated as a conditioning variable, not a stand-alone trade rule. It becomes far more useful when it agrees with the broader macro, liquidity, and risk backdrop.
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Market Agents
This tab answers four questions in order: (1) Who is driving? (2) Are they in conflict? (3) Is the rally funded by liquidity? (4) Is systematic leverage still supported by vol structure and trend? You get a quick snapshot (gauges), then context (charts), then action (signals).
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Market Positioning
Five gauges that approximate the “seat power” of each agent type right now. They’re designed to be interpretable and stable (z-scored against history), not noisy.
Current Player Positioning
A compact snapshot of which market-agent proxy is most stretched right now.
View detailed interpretation...
Understanding Current Player Positioning
These gauges are built from engineered composite indices in the metadata/composites layer. Each raw proxy basket is standardized with a rolling z-score and then pushed through a sigmoid transform to produce a stable 0–100 score. That means the gauges tell you how unusually strong each agent’s proxy behavior is relative to its own history.
- Institutions: quality/value style preference proxies.
- Retail: high-beta relative to low-vol, adjusted by VIX.
- Hedge Funds: the gauge combines cross-asset positioning proxies such as AUDJPY and LQD/IEF, while the charts below separate the signal into volatility term structure, CTA trend, and funding support.
- Passive: high correlation and low dispersion regime proxy.
- Fed: liquidity conditions transformed into a 0–100 funding score.
Scores above 80 across many agents usually mean the market is crowded, not automatically healthy. The value is in the mix and the divergences that follow.
Institutional vs Retail Divergence
Turning points often happen when Retail and Institutions disagree. This chart highlights handoffs: distribution (pros sell to the crowd) vs accumulation (pros buy the panic).
Tip: Tops often show retail strength while institutional activity weakens. Bottoms often show institutional activity improving before retail confidence returns.
Institutional vs Retail
Large gaps indicate positioning conflict and more asymmetric future risk.
View detailed interpretation...
Understanding Institutional vs Retail
The institutional index is built from style spreads that are meant to reflect slower-moving professional accumulation/distribution behavior. The retail index is built from SPHB/SPLV and adjusted for VIX, so it behaves more like a speculative-euphoria proxy. Both are transformed into the same 0–100 scoring framework.
- Institutions up, retail down: accumulation regime; pros are stepping in while the crowd is still cautious.
- Institutions down, retail up: distribution regime; the crowd is chasing while smarter money is reducing risk.
- Both up: healthier broad participation, though it can still become crowded.
The signal is strongest when the lines diverge persistently and then begin to cross back through each other.
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Active Managers vs Retail (NAAIM vs AAII)
Absolute levels matter less than divergence: retail euphoria + manager de-risking = distribution risk.
View detailed interpretation...
Understanding NAAIM vs AAII
Unlike the composite divergence chart above, this one uses two more direct sentiment/exposure inputs. NAAIM exposure approximates how active managers are positioned, while the AAII bull-bear spread captures the retail mood balance between optimism and pessimism.
- AAII high while NAAIM falls: crowd optimism is not being matched by professional exposure.
- Both rising: risk appetite is broad-based.
- Both washed out: pessimism is broad, which can improve contrarian setups later.
AAII Sentiment Composition
Bullish + Neutral + Bearish should sum to 100%. Use this to spot sentiment extremes and transitions.
View detailed interpretation...
Understanding AAII Sentiment Composition
This chart breaks AAII sentiment into its three underlying shares: bullish, neutral, and bearish. The areas sum to 100%, so you can see how sentiment is being reallocated rather than just looking at the net spread.
- Bearish share dominant: fear is explicit and broad.
- Bullish share dominant: optimism is widespread and may become crowded if it persists.
- Neutral collapsing into bullish or bearish: sentiment is leaving the fence and turning directional.
Speculator Confirmation & Liquidity
The hedge-fund read combines volatility term structure, trend-following behavior, funding support, and cross-asset relative-value proxies so the signal can be interpreted from both systematic and market-based angles.
Systematic Speculator Confirmation
A hedge-fund positioning proxy built from volatility term structure, CTA trend, and funding / credit support.
View detailed interpretation...
Understanding Systematic Speculator Confirmation
This chart standardizes three legs into a common rolling z-score framework: VIX term structure (VIX3M - VIX), CTA trend support (S&P 500 versus its 200-day moving average), and a funding / credit support leg based on inverted credit stress.
- All three rising: the short-vol and trend complex is mechanically supportive of risk-taking.
- Contango flips or CTA trend rolls below zero: systematic leverage becomes more fragile and de-grossing risk rises.
- Funding support fades first: the tape can still levitate briefly, but the regime becomes easier to break.
This is still a proxy, not a balance-sheet ledger, but it is designed to map more directly to the mechanics that often shape systematic and leveraged positioning.
Options Surface Risk Proxy
SKEW plus VIX term structure gives an honest options-surface backdrop without pretending to measure dealer gamma directly.
View detailed interpretation...
Understanding the Options Surface Proxy
SKEW rises when downside tail hedging becomes more expensive, while VIX term structure tells you whether the volatility backdrop remains supportive. Together they help you separate a benign options regime from one where hedging demand is intensifying.
- High SKEW + flattening / negative term structure: stress is building under the surface.
- Low-to-moderate SKEW + healthy positive term structure: options conditions are still broadly supportive.
- Sudden SKEW jump with term-structure collapse: risk can transition quickly from grind-up to forced de-risking.
Cross-Asset Confirmation vs Liquidity
A secondary confirmation chart: liquidity is the fuel (area), while the cross-asset leverage composite is the fire (line).
View detailed interpretation...
Understanding Cross-Asset Confirmation vs Liquidity
This chart compares two composite 0–100 indices: hedge-fund leverage and Fed liquidity. The hedge-fund leg is best interpreted as a cross-asset positioning and relative-value confirmation tool, built from relationships such as AUD/JPY and LQD/IEF.
- Both rising: cross-asset positioning is being funded by improving liquidity.
- Positioning high, liquidity down: confirmation is deteriorating and the regime becomes easier to unwind.
- Cross-asset proxies softer, but the systematic chart stays firm: positioning support is being expressed more clearly through the systematic inputs.
Because both axes are normalized, read this as a regime relationship rather than a literal measure of leverage dollars or liquidity dollars.
Passive Flow Regime
When passive dominates, correlation rises and dispersion falls. That’s great for index exposure, bad for stock-picking.
Passive Flow Regime (Correlation)
Low tide = stock pickers’ market. High tide = index melt-up.
View detailed interpretation...
Understanding the Passive Flow Regime
The passive-tide composite is built as a blend of higher correlation and lower market/sector dispersion, then scaled into a 0–100 score. It is not measuring ETF flows directly; it is measuring the kind of market structure passive dominance tends to create.
- High tide: high co-movement, compressed dispersion, and stronger index-level behavior.
- Low tide: more room for stock-picking and idiosyncratic winners/losers.
- Persistent high tide: rallies can look smooth, but breadth and diversification quality often deteriorate.
Conflict Signals (Action Layer)
These traffic lights compress the whole tab into two actionable warnings. Use them as a “risk dashboard” (hedge / reduce / add), not as a standalone trading system.
Signal A
Smart Money Distribution
Pros selling while Retail buys is a fragile regime.
Signal B
Liquidity Danger
Leverage up vs liquidity down increases crash risk.
Crash Probability: Individual vs Institutional
Yale ICF crash-probability surveys for both cohorts. Pairs the institutional crash signal (already present in the Behavioural tab) with the individual cohort that was previously missing here.
Crash Probability Divergence
Individual (amber) vs Institutional (blue). Watch when the two cohorts disagree.
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Understanding the Crash Divergence
Each line is the perceived probability (0–1) of a one-day equity-market crash within the next six months, separately for individual investors and institutional investors in the Yale ICF survey. Levels matter, but the gap between cohorts often matters more.
- Institutional > Individual: pros are more worried than the crowd. Late-cycle pattern; hedging demand is concentrated at the institutional end.
- Individual > Institutional: the crowd is paying for tail risk that pros do not see. Often coincides with capitulation episodes.
- Both up together: consensus stress. Usually accompanies real risk-off regimes elsewhere on the dashboard.
Manager Disagreement (NAAIM dispersion)
NAAIM mean exposure with cross-sectional standard deviation. High dispersion = active managers disagree, often a precursor to regime changes.
NAAIM Mean Exposure vs Dispersion
Mean exposure on the left axis, cross-sectional σ on the right axis (dotted red).
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Understanding NAAIM Dispersion
The blue line is the published NAAIM mean exposure. The dotted red line is the standard deviation of the underlying responses — i.e. how much active managers disagree about the right level of equity exposure that week.
This is more informative than mean exposure alone. A flat mean with rising dispersion means the survey is hiding a building disagreement: some managers are aggressively long while others are de-risking. Historically, that condition tends to precede a regime change in the price.
- Mean low, σ high: consensus is bearish but with many dissenters — contrarian setups become more interesting here.
- Mean high, σ high: consensus is bullish but fragile; positioning is less synchronised than the headline implies.
- Both σ and mean falling: orderly de-risking; managers are coordinating their reduction.
Agent Snapshot (Radar)
A single “shape” view of market drivers. Filled = current. Outlines = 1M, 3M, 6M, and 1Y ago. Bigger area means more agents are simultaneously “active”.
Driver Radar
Institutions • Retail • Hedge Funds (cross-asset proxy lens) • Passive • Fed Liquidity (0–100)
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Understanding the Driver Radar
The radar brings the five normalized agent indices into one visual shape. It answers a simple question: is the market currently being driven by many aligned forces, or by just one or two unusually dominant agents?
- Large, round current shape: many agents are active at once; the regime can be powerful but also crowded.
- Narrow spike in one direction: leadership is concentrated in one driver and can reverse abruptly if that driver fades.
- Current shape shrinking versus older outlines: the prior regime is losing force.
Methodology & Inputs
Show / Hide Detailed Guide
This tab models markets as a tug-of-war between investor groups (“agents”). Because we can’t observe their trades directly, we use behavioral proxies: spreads, ratios, and regime indicators that historically reflect how each group behaves.
Data sources
Yahoo Finance (core, free): style ETFs (QUAL, VLUE, MTUM), risk-on/off ETFs (SPHB, SPLV), credit ETFs (LQD, IEF), sector ETFs, FX (AUDJPY=X), and the S&P 500 trend proxy.
Internal Liquidity Engine: composite of central bank balance sheets, reserves, and funding stress proxies.
Optional (if available): Cboe indices and options-surface proxies such as SKEW and VIX term structure.
How each agent index is constructed
hf_credit_spread input: in this dataset it is an internally normalised funding-stress proxy (typical range ~0.7–1.2), not a basis-points credit spread. The systematic speculator chart enters it as −hf_credit_spread so that lower funding stress → higher score. If hf_credit_spread is unavailable for a date, the proxy falls back to the inverted broad NFCI to avoid masking the signal.
Scaling and interpretation
Each raw proxy is standardized using rolling statistics (z-scores), then rescaled to a 0–100 index.
Values near 0 indicate low participation / risk-off behavior; values near 100 indicate unusually strong participation / risk-on behavior.
These are regime indicators, not direct measures of dollars invested by each group.
Loading Global Policy Divergence...
Global Policy Divergence
This tab tracks the rates-plus-FX transmission channel and the European stress canary. Use it to see when central-bank divergence is tightening global liquidity or turning a local sovereign spread problem into global risk.
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1. Policy Error Gauge
(EA 10Y − US 10Y) spread (Left) vs Broad USD Index (Right).
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Understanding the Policy Error Gauge
The chart is built from two series that the frontend derives directly from the daily dataset. The purple line is the percentage-point spread between the euro-area 10-year government benchmark yield and the US 10-year Treasury yield, computed as (EA10Y - US10Y) * 100. The blue line is the broad USD index. The chart does not infer policy qualitatively; it shows how the market prices the relative stance of the two blocs through long-duration rates and the exchange rate.
A wider yield gap can reflect relatively tighter policy, stronger growth expectations, or higher term premium in Europe versus the US. The dollar line is the transmission channel: if the relative-rates gap and the dollar rise together, global borrowers face a double squeeze through higher discount rates and tighter USD funding conditions.
- Wider gap + stronger USD: the cross-border impulse is usually risk-off. It tends to pressure EM assets, multinational earnings translation, and anything funded in dollars.
- Wider gap + softer USD: the rates story is more locally contained. Divergence exists, but global liquidity is not tightening as aggressively.
- Narrowing gap + weaker USD: cross-Atlantic conditions are converging and the external financing backdrop is usually easing.
Use it as a macro transmission chart rather than a directional trading signal on its own. The important question is not just “who yields more,” but whether FX is amplifying or damping that policy divergence.
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2. European Fragmentation Risk
Italy–Germany 10Y spread (Left, bps) vs Systemic Stress Index (Right).
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Understanding European Fragmentation Risk
This panel combines two distinct but related inputs. The red series converts the Italy minus Germany 10-year sovereign spread into basis points with spread * 10,000. The grey line plots EA CISS, a systemic stress indicator. Together they answer a practical question: is sovereign stress isolated, or is it spilling into the broader European financial system?
Italy versus Germany works as a simple fragmentation proxy because Germany is the core risk-free anchor inside the euro area, while Italy is more sensitive to fiscal, refinancing, and policy credibility concerns. The spread shows the market price of that credit/fragmentation premium. The stress index then tells you whether that premium is staying local or spreading into funding, credit, and volatility conditions.
- Spread up + stress up: contagion risk is increasing. This is the combination most likely to bleed into broader European and global risk assets.
- Spread up but stress flat: the market is ring-fencing the issue so far. Policymakers may still be containing it.
- Spread down + stress easing: fragmentation fears are fading and the euro-area backdrop is normalizing.
The level matters less than the co-movement. What makes this chart useful is the confirmation between sovereign pricing and the broader financial-stress regime.
3. Real Rate Divergence
European real rate (Policy − Core Inflation) vs US Forward Real Yield (10Y − Breakeven), plus the spread.
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Understanding Real Rate Divergence
This chart compares the effective real rate backdrop of each region rather than their nominal yields. The European line is calculated in the frontend as (ECB main refinancing rate − euro-area core inflation) × 100. The US line uses the already engineered real_yield_forward series, which is a forward-looking real-yield proxy based on Treasury yields minus breakeven inflation, also displayed in percent terms. The bars are simply Europe minus US.
Important asymmetry: the two series are not constructed the same way. The European real rate uses the policy rate minus realised core inflation — i.e. it is backward-looking (it tells you how restrictive policy was relative to the inflation that just happened). The US real rate uses the 10-year nominal yield minus 10-year breakeven inflation — it is forward-looking (it tells you how restrictive markets price the next decade to be). Both answer the question "how restrictive is the real-rate environment?" but they answer it through different windows. The directional read of the spread is robust; do not over-interpret small level differences as identical-meaning numbers.
Why compare policy-minus-inflation in Europe with a market real yield in the US? Because both series answer the same economic question: how restrictive is the real rate environment facing capital, credit, and duration-sensitive assets?
- European line above the US line: Europe is running tighter real conditions. That can matter for FX, cross-border capital allocation, and relative earnings pressure.
- US line above Europe: the US is offering the tighter real-rate anchor, which often supports the dollar and raises the global discount-rate hurdle.
- Rapid spread reversals: the regime is changing. These turns often show up in FX and rate-sensitive sectors before they become obvious in broad equity indices.
Treat this chart as a relative policy-stance map. It is most useful when read alongside the dollar and fragmentation charts above, because real-rate divergence becomes more powerful when FX and credit channels confirm it.
4. USD vs Gold
DXY (left axis) against gold (right axis). When the dollar strengthens but gold doesn't fall, the dollar move is being interpreted as growth fear rather than rate divergence.
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Understanding USD vs Gold
The blue line is the DXY (US Dollar Index). The amber line is the price of gold in USD per ounce. They are plotted on a dual axis because their levels are not directly comparable, but their directional co-movement is the signal.
In a typical rate-divergence regime, dollar and gold move opposite each other: a stronger dollar means higher US real rates, which compresses gold. The interesting and tradeable cases are when that relationship inverts.
- DXY up, gold down: classic rate-divergence regime. The dollar is strengthening because US real rates are rising, and gold is responding to the higher opportunity cost.
- DXY up, gold up: growth-fear or geopolitical regime. The dollar is rallying as a safe haven, and gold is rallying for the same reason. Often coincides with risk-off elsewhere on the dashboard.
- DXY down, gold up: reflation / debasement regime. Easier dollar conditions plus inflation expectations.
- DXY down, gold down: rare; usually a short-lived liquidity event where everything is being sold.
5. Real-Rate Spread → FX Response
Scatter: x = (EU − US) real-rate spread in pp, y = EUR NEER (broad euro effective exchange rate). Colour scales with time; star marks the latest observation.
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Understanding the Real-Rate → FX Map
The previous panel shows the real-rate divergence and the policy-error gauge shows how the dollar responds, but they live in different charts. This scatter merges them: each dot is one historical date, plotting the EU − US real-rate spread on the x-axis against the EUR NEER (broad effective exchange rate) on the y-axis. The colour gradient encodes time so you can see how the relationship has migrated.
The expected economic relationship is positive: tighter real conditions in Europe → stronger euro → higher EUR NEER. The interesting cases are when the regime departs from that relationship — for example, when EUR NEER stays elevated even as the real-rate spread compresses (FX is overshooting fundamentals), or when EUR NEER refuses to rally even as the spread widens (a different story is dominating, often capital-account flows or sovereign-fragmentation fear).
- Latest star top-right: EU real rates are higher than US and the euro is strong — the textbook regime.
- Latest star bottom-left: US real rates are higher and the euro is weak — also textbook.
- Latest star bottom-right: EU offers higher real rates but the euro is still weak. Usually means flow effects (e.g. fragmentation premium, energy-imports drag) are dominating the rate signal.
- Latest star top-left: US offers higher real rates yet the euro is strong. Often a positioning unwind or risk-on regime where carry stops dominating.
This panel is more actionable than reading the divergence and the dollar separately because it shows whether the FX market is actually responding to the rate divergence in the way classical theory predicts.