Saqrid Learn: a quant and options glossary
Definitions, formulas and common mistakes for the options, volatility, statistical and cross-asset concepts used across Saqrid, written for traders who want the maths as well as the intuition.
SVQ: options and volatility
Dealer positioning
- Gamma exposure (GEX)Gamma exposure (GEX) estimates how much options dealers may need to buy or sell to stay hedged as the underlying price moves.
- Gamma flip (gamma balance point)The gamma flip is the underlying price at which estimated net dealer gamma crosses zero, separating damping from amplifying hedge flows.
- Same-day expiry (0DTE) optionsSame-day expiry (0DTE) options expire on the day they trade, so their gamma, time decay and delta decay are far larger than on longer-dated options.
Greeks
- CharmCharm, or delta decay, measures how an option's delta changes as time passes with price and volatility held fixed.
- VannaVanna is the second-order options Greek that measures how an option's delta changes when implied volatility changes, or equally how vega changes with spot.
- Volga (vomma)Volga, also called vomma, measures how an option's vega changes as implied volatility changes: the convexity of option value in volatility.
No-arbitrage
- Butterfly arbitrageButterfly arbitrage exists when option prices are not convex in strike, so a butterfly spread would cost less than zero to own.
- Calendar arbitrageCalendar arbitrage arises when total implied variance falls as expiry lengthens at the same moneyness, implying a calendar spread with negative cost.
- Durrleman conditionThe Durrleman condition tests whether an implied variance smile implies a non-negative probability density, the smile form of no butterfly arbitrage.
Option-implied distributions
- Risk-neutral density (Breeden–Litzenberger)The risk-neutral density is the probability distribution of the future underlying price implied by option prices, recovered from their curvature in strike.
Pricing
- Options fair value vs quotesAn option's fair value is a model price from a fitted volatility surface; a quote is what someone will trade at. Only the quote is tradeable.
Surface models
- SSVI (surface SVI)SSVI extends SVI from one expiry to a whole implied volatility surface, with explicit conditions that rule out butterfly and calendar arbitrage.
- SVI parameterizationSVI is a five-parameter formula for one expiry's implied total variance that fits equity smiles well and has known no-arbitrage conditions.
Volatility
- IV rankIV rank places current implied volatility within its own past range, from 0 at the period low to 100 at the period high.
- Volatility risk premium (VRP)The volatility risk premium is the typical gap between implied volatility and the volatility that is later realized, a price for bearing volatility risk.
Volatility surface
- Implied volatility surfaceAn implied volatility surface maps the implied volatility of options across strike (or moneyness) and time to expiry for one underlying.
- Put skew and crash riskPut skew is the extra implied volatility on downside strikes, a market price for crash risk that rises when demand for protection grows.
- Volatility smile and skewThe volatility smile and skew describe how implied volatility varies with strike for a single expiry, revealing how the market prices tail moves.
SV: statistical charting
Chart types
- Range barsRange bars close when price has traveled a fixed distance rather than when a fixed amount of time has passed, removing time from the horizontal axis.
Foundations
- Log returnsA log return is the natural log of the price ratio between two dates; log returns add across time, which makes them the default unit in quant work.
- Statistical indicatorsA statistical indicator estimates a defined property of returns, such as volatility, memory or a probability, rather than applying a fixed chart rule.
Regimes
- Hidden Markov model regimesA hidden Markov model treats market regimes as unobserved states that switch over time, each with its own return and volatility behavior.
Statistical indicators
- Expected moveThe expected move is the size of price change that options imply over a horizon, usually derived from implied volatility or the at-the-money straddle.
- Hurst exponentThe Hurst exponent measures long-range memory in a time series: about 0.5 for a random walk, above for persistent trends, below for mean reversion.
- Probability coneA probability cone projects a range of future prices that widens with the square root of time, scaled by volatility and a chosen confidence level.
- Shannon entropy in marketsShannon entropy measures how uncertain a distribution of outcomes is; applied to returns or price patterns, it gauges how disordered a market is.
Volatility estimators
- GARCHGARCH models volatility that clusters: today's variance depends on yesterday's squared shock and yesterday's variance, reverting to a long-run level.
- Realized volatilityRealized volatility measures how much an asset actually moved; close-to-close, Parkinson, Garman–Klass and Yang–Zhang estimators use different price data.
SVPulse: prediction markets and macro context
Cross-asset risk
- Market volatility gaugeA market volatility gauge combines several standardized stress measures, such as implied volatility, correlation and spreads, into one composite reading.
- Volatility spilloverVolatility spillover is the transmission of volatility shocks from one asset or market to others, measured with VAR, GARCH or information-flow models.
Macro events
- Economic catalyst calendarAn economic catalyst calendar lists scheduled market-moving events, such as FOMC decisions, CPI, PCE and payrolls releases, and options expirations.
- Shipping chokepoints and market riskShipping chokepoints are narrow sea passages carrying a large share of world trade and energy; disruption there can move oil, freight and inflation views.
Prediction markets
- Prediction market analysisPrediction market analysis reads the prices of event contracts as crowd probabilities and checks them for liquidity, resolution rules and bias.
- Prediction market odds as probabilitiesA prediction market price can be read as an implied probability, but spreads, fees, overround and longshot bias mean it needs adjusting first.
SVNexus: regimes and cross-asset contagion
Contagion
- Correlation networksA correlation network represents assets as nodes and their dependence as weighted links, making clusters and central assets visible.
- Cross-asset contagionCross-asset contagion is a rise in linkages between markets after a shock, beyond normal interdependence, so losses spread further than usual.
- Diebold–Yilmaz connectednessThe Diebold–Yilmaz index measures how much of each market's forecast-error variance comes from shocks to other markets, summarized as total connectedness.
Dependence
- DCC correlationDynamic conditional correlation (DCC) models correlations that change over time, built on GARCH volatilities for each asset.
- Tail dependenceTail dependence measures the chance that two assets suffer extreme moves together, which ordinary correlation can understate badly.
- Transfer entropyTransfer entropy measures directed information flow: how much one series' past reduces uncertainty about another's next value, beyond its own past.
Regimes
- Bubble detection (explosive-root, GSADF)Explosive-root tests such as SADF and GSADF look for periods where prices grow faster than a random walk allows, a statistical signature of bubbles.
- Change-point detection (BOCPD)Change-point detection finds dates where a series' behavior shifts; Bayesian online change-point detection (BOCPD) tracks the current regime's age.
- Market regime detectionMarket regime detection classifies periods into states such as calm, trending or stressed, so analysis and risk can adapt to conditions.
SVE: execution and paper trading
Execution
- Bracket orders (take-profit / stop-loss)A bracket order pairs a position with a take-profit and a stop-loss exit; when one exit fills, the other is canceled automatically.
- Paper tradingPaper trading means placing simulated orders against market prices without committing capital, to practice execution and test a process.
Market microstructure
- Order book depthOrder book depth shows how much size is resting at each price on the bid and ask sides, which determines how far a large order would move price.
Quant foundations
Foundations
- Quantitative analysisQuantitative analysis studies markets with data, statistics and mathematical models, turning ideas into testable, measurable claims.
- Statistical analysis in tradingStatistical analysis in trading tests whether an observed pattern in returns is distinguishable from chance, and how large and stable it is.
Educational definitions written for a quantitative audience. Nothing here is investment advice or a recommendation to trade.