Volatility

Volatility surface

Returns coin-level volatility surface options-volatility-landscape. One row per (coin, timestamp). The single most comprehensive endpoint in the API: 127 columns covering ATM IV across 4 tenors, term structure dynamics, put/call skew per tenor, smile metrics, surface quality assessment, realized volatility (3 windows), variance risk premium (3 windows + regime + percentiles), cross-asset IV correlation, IV regime classification, and 6 layers of proprietary ORIA intelligence: from RV stress and breach detection through skew contagion, cross-asset relative value, dynamic signal processing, to the vol lifecycle state machine that no competitor offers.

GET/v1/vol/surfaceproalpha

Query Parameters

coinstringrequired

Underlying asset. Required.

e.g.BTCETHSOL

fromstringoptional

Start UTC (ISO 8601). Default: latest snapshot.

e.g.2026-03-01T00:00:00Z

tostringoptional

End UTC (ISO 8601). Default: now.

e.g.2026-03-09T00:00:00Z

limitintegeroptional

Max rows returned. Default 500, max 5000.

e.g.5004320

Response Schema

Fields marked pro require a Pro subscription. Fields marked alpha require Alpha.

Field	Type	Tier	Description
`timestamp`	`datetime`	pro	Snapshot time in UTC. Aligned to 10-minute boundary.
`coin`	`string`	pro	Underlying asset (BTC, ETH, SOL, XRP, AVAX, TRX).
`atm_iv_dte_7`	`float`	pro	ATM implied volatility (pct) for 0-7 DTE bucket. Weekly expiry reference.
`atm_iv_dte_30`	`float`	pro	ATM IV for 8-30 DTE. The most-watched tenor.
`atm_iv_dte_60`	`float`	pro	ATM IV for 31-60 DTE. Quarterly reference.
`atm_iv_dte_long`	`float`	pro	ATM IV for 60+ DTE. Structural vol level.
`term_structure_slope`	`float`	pro	Is vol in contango or backwardation? The term structure slope. See detail ↓
`term_structure_spread`	`float`	pro	Absolute spread: dte_long IV minus dte_7 IV in vol points.
`term_structure_shape`	`string`	pro	CONTANGO (normal upward), BACKWARDATION (inverted, fear), FLAT, HUMPED.
`term_slope_change_1h`	`float`	pro	Term slope change vs 1 hour ago.
`term_slope_change_24h`	`float`	pro	Term slope change vs 24 hours ago.
`term_slope_percentile_30d`	`float`	pro	Where the current slope sits in 30-day history. Below 10 = unusually flat/inverted.
`put_skew_dte30`	`float`	pro	Put skew at 30d: FAR_BELOW IV minus ATM IV. The industry standard fear gauge.
`put_skew_dte7`	`float`	pro	Put skew at 7d. Front-end fear. Spikes into events.
`put_skew_dte60`	`float`	pro	Put skew at 60d. Structural downside pricing.
`call_skew_dte30`	`float`	pro	Call skew at 30d: FAR_ABOVE IV minus ATM IV. Upside demand.
`call_skew_dte7`	`float`	pro	Call skew at 7d.
`call_skew_dte60`	`float`	pro	Call skew at 60d.
`skew_ratio_dte30`	`float`	pro	Put/call skew ratio at 30d. Above 1 = fear dominant. Below 1 = greed dominant.
`smile_width_dte30`	`float`	pro	Smile convexity at 30d: (FAR_BELOW + FAR_ABOVE) - 2*ATM. Higher = more tail premium.
`put_skew_change_24h`	`float`	pro	Put skew change vs 24 hours ago.
`skew_percentile_30d`	`float`	pro	Where put skew sits in 30-day history.
`skew_momentum_direction`	`string`	pro	STEEPENING (fear increasing), FLATTENING (fear decreasing), STABLE.
`surface_avg_iv`	`float`	pro	Liquidity-weighted average IV across the entire surface.
`surface_median_iv`	`float`	pro	Median IV across all cohorts. Robust to outliers.
`surface_iv_dispersion`	`float`	pro	Standard deviation of IV across cohorts. High dispersion = fragmented surface.
`surface_iv_range`	`float`	pro	Max minus min IV on the surface.
`surface_liquidity_score`	`float`	pro	Average liquidity score across the surface (0-100).
`active_cohort_count`	`integer`	pro	Number of cohorts (out of 28) with valid data.
`surface_avg_divergence_pct`	`float`	pro	Mean divergence between market and theoretical prices across all cohorts.
`surface_max_divergence_pct`	`float`	alpha	Worst divergence on the surface. Red flag if high.
`surface_median_divergence_pct`	`float`	alpha	Median divergence. Robust quality measure.
`high_stress_cohort_count`	`integer`	alpha	Cohorts with HIGH_STRESS conditions. Above 5 = surface-wide execution concerns.
`moderate_stress_cohort_count`	`integer`	alpha	Cohorts with MODERATE_STRESS.
`normal_conditions_cohort_count`	`integer`	alpha	Cohorts with NORMAL_CONDITIONS.
`institutional_grade_cohort_count`	`integer`	alpha	Cohorts at INSTITUTIONAL_GRADE quality.
`professional_grade_cohort_count`	`integer`	alpha	Cohorts at PROFESSIONAL_GRADE.
`research_grade_cohort_count`	`integer`	alpha	Cohorts at RESEARCH_GRADE.
`monitor_only_cohort_count`	`integer`	alpha	Cohorts at MONITOR_ONLY (untradeable).
`extreme_divergence_cohort_count`	`integer`	alpha	Cohorts with EXTREME_DIVERGENCE.
`high_divergence_cohort_count`	`integer`	alpha	Cohorts with HIGH_DIVERGENCE.
`aligned_cohort_count`	`integer`	alpha	Cohorts with ALIGNED (divergence < 2 pct).
`surface_quality_tier`	`string`	pro	INSTITUTIONAL_GRADE, PROFESSIONAL_GRADE, RESEARCH_GRADE, or MONITOR_ONLY.
`surface_execution_recommendation`	`string`	pro	AGGRESSIVE (tight surface, low stress), STANDARD, CAUTIOUS, AVOID.
`surface_avg_execution_difficulty`	`float`	alpha	Mean execution difficulty score (0-100) across the surface.
`surface_max_execution_difficulty`	`float`	alpha	Worst execution difficulty on the surface.
`realized_vol_7d`	`float`	pro	7-day annualized realized volatility from spot returns.
`realized_vol_30d`	`float`	pro	30-day annualized RV. The standard benchmark for VRP calculation.
`realized_vol_90d`	`float`	pro	90-day annualized RV. Long-term reference.
`rv_change_7d`	`float`	pro	RV change vs 7 days ago. Rising RV = vol expanding.
`rv_percentile_30d`	`float`	pro	Where RV sits in 30-day history.
`vrp_atm_vs_rv7d`	`float`	pro	VRP: ATM IV (30d) minus RV (7d). Shortest RV window, most reactive.
`vrp_atm_vs_rv30d`	`float`	pro	The Variance Risk Premium: should you sell vol or buy vol? See detail ↓
`vrp_atm_vs_rv90d`	`float`	pro	VRP: ATM IV (30d) minus RV (90d). Most stable reference.
`vrp_percentile_30d`	`float`	pro	Where VRP sits vs 30-day history.
`vrp_percentile_90d`	`float`	pro	Where VRP sits vs 90-day history.
`vrp_regime`	`string`	pro	RICH (positive VRP, sell vol), FAIR (near zero), CHEAP (negative VRP, buy vol).
`vrp_zscore`	`float`	pro	VRP in standard deviations from mean. Beyond +/-2 = extreme.
`iv_correlation_btc_7d`	`float`	pro	IV correlation with BTC (7-day rolling). High = coin IV moves with BTC.
`iv_correlation_btc_30d`	`float`	pro	IV correlation with BTC (30-day rolling).
`iv_beta_to_btc`	`float`	pro	IV beta: regression slope vs BTC IV. Above 1 = amplifies BTC vol moves.
`iv_spread_vs_btc`	`float`	pro	This coin ATM IV minus BTC ATM IV. The vol premium over BTC.
`coin_iv_percentile_7d`	`float`	pro	Surface avg IV vs 7-day history.
`coin_iv_percentile_30d`	`float`	pro	Surface avg IV vs 30-day history.
`coin_iv_percentile_52w`	`float`	pro	IV Rank (annual). Below 20 = historically low IV.
`coin_iv_regime`	`string`	pro	LOW, NORMAL, HIGH, EXTREME based on percentile position.
`rv_stress_regime`	`string`	pro	NORMAL, MODERATE_STRESS, HIGH_STRESS, EXTREME_STRESS based on RV change magnitude.
`breach_rate_7d`	`float`	pro	Fraction of cycles IV breached RV bands (7d). High breach rate = vol is breaking its range.
`breach_rate_30d`	`float`	pro	Breach rate over 30 days.
`upside_breach_rate_7d`	`float`	alpha	Fraction of upside breaches (7d). IV expanding above RV.
`downside_breach_rate_7d`	`float`	alpha	Fraction of downside breaches (7d). IV collapsing below RV.
`breach_direction_bias`	`float`	alpha	Upside minus downside breach rate. Positive = IV expanding, negative = compressing.
`breach_regime`	`string`	pro	CONTAINED (few breaches), MIXED, PERSISTENT, EXTREME.
`vov_7d`	`float`	pro	Annualized vol of ATM IV changes (7d). How unstable is IV itself.
`vov_30d`	`float`	pro	VoV over 30 days.
`vov_regime`	`string`	pro	STABLE, ELEVATED, ERRATIC, EXTREME. ERRATIC = vega risk is high.
`gamma_carry_pnl_1d`	`float`	pro	1-day gamma vs theta carry. Positive = gamma winning (realized moves exceed IV). Negative = theta winning (quiet market).
`gamma_carry_pnl_7d`	`float`	pro	7-day rolling gamma carry.
`gamma_carry_regime`	`string`	pro	GAMMA_WINNING, BALANCED, THETA_WINNING.
`iv_responsiveness_7d`	`float`	alpha	Ratio of IV change to spot change. High = IV reacts quickly (efficient pricing). Low = lagging (mispriced).
`iv_responsiveness_regime`	`string`	alpha	RESPONSIVE, NEUTRAL, LAGGING.
`regime_multiplier`	`float`	alpha	Composite confidence multiplier for signal weighting. Higher = stronger signal confidence.
`percentile_confidence`	`string`	alpha	RELIABLE, UNCERTAIN, UNRELIABLE. Based on data depth for percentile calculations.
`skew_level_divergence`	`string`	alpha	ALIGNED (skew and IV level agree), DIVERGENT, CONTRADICTORY.
`skew_level_divergence_score`	`float`	alpha	Numeric divergence score (0-100).
`rv_concentration_ratio`	`float`	alpha	Largest daily return squared / sum of all returns squared (7d). Above 0.4 = one event dominates RV. The VRP calculation is contaminated.
`days_until_shock_rollout`	`integer`	alpha	Days until the dominant shock exits the 7d RV window. Countdown to RV normalization.
`rv_ex_shock`	`float`	alpha	7d RV recalculated excluding the largest return. The clean VRP denominator.
`skew_term_slope`	`float`	pro	Is fear concentrated in the front end or the back end? See detail ↓
`skew_term_shape`	`string`	pro	FRONT_LOADED_FEAR (DTE_7 skew >> DTE_60), NORMAL, BACK_LOADED_FEAR.
`skew_elasticity_24h`	`float`	alpha	Skew mean-reversion speed (24h). Higher = skew snaps back quickly (elastic). Lower = skew changes persist (sticky).
`skew_max_excursion_24h`	`float`	alpha	Maximum skew swing over 24 hours. The realized range of skew.
`skew_elasticity_regime`	`string`	alpha	ELASTIC (skew mean-reverts fast), MODERATE, STICKY (skew changes persist), QUIET (small moves).
`skew_contagion_score`	`float`	alpha	Cross-tenor alignment: 0 (no contagion), 60 (partial), 100 (full). When all tenors steepen simultaneously, fear is systemic.
`skew_contagion_regime`	`string`	alpha	NO_CONTAGION, PARTIAL_CONTAGION, FULL_CONTAGION.
`front_end_skew_velocity`	`string`	alpha	DTE_7 velocity regime from cohort_iv_skew. The fastest-moving skew signal.
`inversion_duration_cycles`	`integer`	alpha	Consecutive 10-min cycles in BACKWARDATION. Longer = more entrenched fear.
`inversion_depth_percentile`	`float`	alpha	Current inversion depth vs 90-day inversion history.
`inversion_regime`	`string`	alpha	NORMAL, SHALLOW_INVERSION, DEEP_INVERSION, EXTREME_INVERSION.
`iv_spread_vs_btc_dte7`	`float`	alpha	IV spread vs BTC at DTE_7. NULL for BTC (benchmark).
`iv_spread_vs_btc_dte60`	`float`	alpha	IV spread vs BTC at DTE_60.
`iv_spread_vs_btc_long`	`float`	alpha	IV spread vs BTC at DTE_LONG.
`vol_spread_term_slope`	`float`	alpha	Slope of the IV spread across tenors. How the premium vs BTC changes with maturity.
`vol_spread_term_shape`	`string`	alpha	FRONT_HEAVY (wider at front), BACK_HEAVY, UNIFORM, INVERTED.
`iv_spread_vs_btc_percentile_30d`	`float`	alpha	Spread percentile vs 30-day history. At extremes = mean-reversion trade.
`iv_spread_vs_btc_zscore`	`float`	alpha	Spread z-score (90d). Beyond +/-2 = statistically extreme.
`iv_spread_regime`	`string`	alpha	WIDE, NORMAL, TIGHT, COMPRESSED. COMPRESSED = vol convergence trade.
`rr_spread_vs_btc_dte7`	`float`	alpha	Risk reversal spread vs BTC at DTE_7.
`rr_spread_vs_btc_dte30`	`float`	alpha	Risk reversal spread vs BTC at DTE_30.
`rr_spread_vs_btc_dte60`	`float`	alpha	Risk reversal spread vs BTC at DTE_60.
`relative_skew_term_slope`	`float`	alpha	Slope of skew spread vs BTC across tenors.
`relative_skew_regime`	`string`	alpha	COIN_BULLISH_VS_BTC (coin skew less fearful), COIN_BEARISH_VS_BTC, NEUTRAL, CONFLICTED.
`eth_skew_leading_signal`	`string`	alpha	ETH only: BULLISH_DIVERGENCE, BEARISH_DIVERGENCE, ALIGNED. ETH skew leads BTC by hours.
`gamma_efficiency`	`float`	alpha	How much gamma do you get per unit of theta paid? See detail ↓
`relative_gamma_value`	`float`	alpha	Gamma efficiency vs BTC - 1. Positive = cheaper gamma than BTC.
`rv_iv_ratio_spread`	`float`	alpha	RV/IV ratio for this coin minus BTC. Positive = coin RV outpaces IV more than BTC.
`orderliness_ratio`	`float`	alpha	Is the market repricing smoothly or in jumps? See detail ↓
`return_kurtosis_24h`	`float`	alpha	Excess kurtosis of 10-min returns (24h). Above 10 = extreme fat tails. Below 3 = thin tails.
`repricing_orderliness_regime`	`string`	alpha	ORDERLY (smooth repricing), CHOPPY, EXTREME_JUMPS (gap risk).
`spot_vol_beta_down`	`float`	alpha	IV change per 1 pct spot selloff. Positive = normal crypto (IV rises on selloff).
`spot_vol_beta_up`	`float`	alpha	IV change per 1 pct spot rally. Negative = normal (IV drops on rally).
`spot_vol_asymmetry_ratio`	`float`	alpha	How much worse is a selloff than a rally for your short vol position? See detail ↓
`breach_sustainability_avg_7d`	`float`	alpha	Average cycles an IV breach persists before mean-reversion (7d). High = trending vol. Low = mean-reverting.
`breach_sustainability_regime`	`string`	alpha	MEAN_REVERTING (sell vol after breach), MODERATE_PERSISTENCE, TRENDING (do not fade breaches).
`flow_spot_correlation_down`	`float`	alpha	Correlation of spot return and net call/put flow during selloffs (7d, sign-flipped). Positive = dip buying.
`behavioral_regime`	`string`	alpha	DIP_BUYING (flow buys on drops), CAPITAL_PRESERVING (flow sells on drops), NEUTRAL.
`vol_lifecycle_phase`	`string`	pro	COMPRESSION (coiled spring, vol low and falling), EARLY_EXPANSION (first signs of breakout), EXPANSION (vol rising), PEAK (vol extreme), STRESS (crash conditions), NORMALIZATION (returning to base). The single most valuable field in the API. No competitor computes this for crypto.
`phase_duration_cycles`	`integer`	alpha	How many 10-min cycles the current phase has persisted. Long COMPRESSION (200+ cycles, ~33h) = coiled spring ready to break.
`phase_confidence`	`float`	alpha	Lifecycle classifier confidence (0-100). Below 50 = phase is ambiguous, do not trade on it.
`compression_duration_days`	`float`	alpha	Days in current COMPRESSION phase (NULL if not in COMPRESSION). Above 20 days = historically extended, breakout imminent.

Derived Fields

FieldTypeTiercollapse all

▶term_structure_slopefloatprocollapse

Is vol in contango or backwardation? The term structure slope.

Ratio of long-dated to short-dated ATM IV minus 1. Positive = contango (normal, long-dated vol higher than short-dated). Negative = backwardation (front-end fear, event pricing). Zero = flat term structure.

Term structure slope

\text{slope} = \frac{\sigma_{\text{ATM}}^{\text{DTE\_LONG}} - \sigma_{\text{ATM}}^{\text{DTE\_7}}}{\sigma_{\text{ATM}}^{\text{DTE\_7}}}

RangeTypically -0.3 to +0.5. Negative = backwardation. Above +0.3 = steep contango.

▶vrp_atm_vs_rv30dfloatprocollapse

The Variance Risk Premium: should you sell vol or buy vol?

ATM implied volatility (30-day tenor) minus 30-day realized volatility. THE number for vol trading. Positive = IV premium exists, vol selling is profitable on average. Negative = IV is cheap relative to realized, consider buying vol. The single most researched signal in volatility literature.

Variance risk premium (ATM vs RV30d)

\text{VRP} = \sigma_{\text{ATM}}^{\text{30d}} - \text{RV}_{\text{30d}}

RangeTypically -10 to +20 vol points. Positive is normal in crypto (IV overprices). Negative = buy vol.

▶skew_term_slopefloatprocollapse

Is fear concentrated in the front end or the back end?

Slope of put skew across DTE buckets, normalized by the 30d midpoint. Positive = back-loaded fear (longer-dated skew steeper, structural concern). Negative = front-loaded fear (near-term event hedging, resolves at expiry).

Skew term structure slope

\text{skew\_term\_slope} = \frac{\text{put\_skew}_{\text{DTE\_60}} - \text{put\_skew}_{\text{DTE\_7}}}{\text{put\_skew}_{\text{DTE\_30}}}

RangeTypically -2 to +2. Positive = BACK_LOADED_FEAR. Negative = FRONT_LOADED_FEAR.

▶gamma_efficiencyfloatalphacollapse

How much gamma do you get per unit of theta paid?

Dollar-gamma normalized efficiency: (RV/IV) scaled by the dollar-gamma alpha from cohort Greeks. Measures how efficiently priced the gamma is. Higher = you are getting more realized movement per dollar of theta paid. Compare across coins: the coin with highest gamma_efficiency offers the best gamma-buying opportunity.

Gamma efficiency (dollar-gamma normalized)

\text{gamma\_eff} = \frac{\text{RV}_{\text{7d}} / \sigma_{\text{ATM}}^{\text{30d}}}{\alpha_{\text{dollar-gamma}}}

▶orderliness_ratiofloatalphacollapse

Is the market repricing smoothly or in jumps?

Ratio of 1-hour RV to 10-minute RV. Above 0.8 = smooth, orderly repricing (IV adjustments are gradual). Below 0.3 = jump-dominated, gap risk (IV adjustments happen in sudden bursts). This directly affects your hedging P&L: smooth repricing = delta hedging works. Jumps = you get gapped.

Repricing orderliness ratio

\text{orderliness} = \frac{\text{RV}_{\text{1h}}}{\text{RV}_{\text{10min}}}

Range0 to 1. Above 0.8 = ORDERLY. Below 0.3 = EXTREME_JUMPS.

▶spot_vol_asymmetry_ratiofloatalphacollapse

How much worse is a selloff than a rally for your short vol position?

Absolute downside beta divided by absolute upside beta. Above 1.5 = IV rises much faster on selloffs than it falls on rallies. This is the P&L asymmetry for premium sellers: your losses on down moves are 1.5-3x larger than your gains on up moves of equal magnitude. The number that separates profitable from unprofitable short vol.

Spot-vol asymmetry ratio

\text{asymmetry} = \frac{|\beta_{\text{down}}|}{|\beta_{\text{up}}|}

RangeTypically 1.0-4.0 in crypto. Above 2.0 = strongly asymmetric (short vol is dangerous).

Suggested Calculations

Not included in the API response. Compute these client-side from the fields above. Formulas and context provided.

FieldTypeInputsexpand all

▶vrp_trade_signalstringclient-sideShould you sell vol or buy vol right now?expand

Should you sell vol or buy vol right now?

The fundamental vol trade: RICH VRP + HIGH/EXTREME IV regime = sell premium (straddles, iron condors). CHEAP VRP + LOW IV regime = buy vol (strangles, calendars). The combination matters: RICH VRP in LOW IV might just mean RV collapsed, not that IV is actually rich. Cross-reference both.

Inputsvrp_regimevrp_atm_vs_rv30dcoin_iv_regime

▶term_structure_regime_readstringclient-sideWhat is the term structure telling you about fear vs complacency?expand

What is the term structure telling you about fear vs complacency?

CONTANGO (positive slope) = normal, market pricing term premium. BACKWARDATION = front-end fear exceeds structural vol, a specific event is causing panic. When term_structure_shape = BACKWARDATION AND vol_lifecycle_phase = COMPRESSION, the market is pricing event risk into the front end while structural vol remains suppressed. This is the setup for the biggest moves.

Inputsterm_structure_shapeterm_structure_slopevol_lifecycle_phase

▶lifecycle_compression_alertstringclient-sideIs vol about to explode? The compression breakout screen.expand

Is vol about to explode? The compression breakout screen.

Filter for vol_lifecycle_phase = COMPRESSION. This is the coiled spring state: vol is low and getting lower, the market is quiet, premiums are cheap. When skew starts STEEPENING during COMPRESSION, someone is buying crash protection before the breakout. This is the highest-conviction pre-positioning signal in vol trading.

Inputsvol_lifecycle_phasesurface_avg_ivskew_momentum_direction

▶carry_regime_assessmentstringclient-sideIs it a good environment for selling premium?expand

Is it a good environment for selling premium?

THETA_WINNING + RICH VRP + STABLE VoV = ideal carry environment. GAMMA_WINNING = realized moves are beating theta, do not sell premium. ERRATIC VoV = vega risk is high, spread positions to reduce vega. This triple check prevents the common mistake of selling vol based on VRP alone without checking if the carry is actually working.

Inputsgamma_carry_regimevrp_regimevov_regime

▶skew_term_divergencestringclient-sideWhere on the curve is the fear concentrated?expand

Where on the curve is the fear concentrated?

FRONT_LOADED_FEAR = DTE_7 skew much steeper than DTE_60. Likely event-driven, resolves at expiry. BACK_LOADED_FEAR = longer-dated skew is steeper. Structural concern. Calendar skew trades profit from FRONT_LOADED_FEAR normalization: sell front-end puts, buy back-end puts.

Inputsput_skew_dte7put_skew_dte30put_skew_dte60skew_term_shape

▶rv_contamination_screenstringclient-sideIs the VRP signal contaminated by a single event?expand

Is the VRP signal contaminated by a single event?

If rv_concentration_ratio > 0.4, one event dominates the RV calculation. The VRP you see is an artifact, not a signal. Use rv_ex_shock as the clean denominator: vrp_clean = atm_iv - rv_ex_shock. Also: days_until_shock_rollout tells you when the contaminated return exits the window and VRP normalizes. Time your entry after rollout.

Inputsrv_concentration_ratiodays_until_shock_rolloutrv_ex_shockvrp_atm_vs_rv30d

▶cross_asset_vol_tradestringclient-sideRelative value vol trade: this coin vs BTCexpand

Relative value vol trade: this coin vs BTC

COMPRESSED spread + z-score below -2 = coin vol is historically cheap vs BTC. Buy coin vol, sell BTC vol (calendar or straddle spread). WIDE spread + z-score above +2 = coin vol is historically rich. Sell coin vol, buy BTC vol. The relative_skew_regime adds directional tilt: COIN_BULLISH_VS_BTC suggests upside vol is cheap on the coin.

Inputsiv_spread_regimeiv_spread_vs_btc_zscorerelative_skew_regime

▶asymmetry_premium_seller_checkstringclient-sideWhat is your real P&L skew as a premium seller?expand

What is your real P&L skew as a premium seller?

spot_vol_asymmetry_ratio > 2.0 means IV rises 2x faster on selloffs than it drops on rallies. Your short vol position has negatively skewed P&L. Combine with breach_sustainability_regime: if TRENDING, breaches persist and your short vol bleed extends. If MEAN_REVERTING, pain is temporary. DIP_BUYING behavioral_regime means flow supports recovery, a better environment for short vol.

Inputsspot_vol_asymmetry_ratiobreach_sustainability_regimebehavioral_regime