Options Data Basic Concepts

Data Reference: Data Structure
Last Updated: 2026-01-20

This document summarizes key concepts from the OptionData product documentation for internal reference. It is organized into foundational concepts, core Greeks & metrics, market structure indicators, and real-time flow analysis. Field names referenced here (e.g., side, sentiment, dex) correspond to the actual data fields documented in Data Structure.

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Table of Contents

1. Quick Reference Tables
   • Trade Execution Side
   • Buy vs Sell: Inferring Trade Direction
   • Sentiment Derivation
   • Trade Activity Types
   • Moneyness Classification
2. Foundational Concepts
   • Data-Driven Trading Strategy
   • Understanding Option Quotes
   • Options Dictionary
3. Core Greeks & Metrics
   • Delta Exposure (DEX)
   • Delta Impact (DEI)
   • Gamma Exposure (GEX)
     • Call Wall vs Put Wall
     • Gamma Squeeze
     • The 0DTE Phenomenon
   • Implied Volatility (IV)
4. Option Chain Analysis
   • Option Chain vs Option Flow
   • Open Interest (OI)
   • Analyzing OI Changes & Trade Intent

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Quick Reference Tables

Trade Execution Side (side field)

The side field indicates where the trade was executed relative to the bid-ask spread:

[!TIP] Side classification logic:

AASK  = price > ask           (Above Ask)
ASK   = price >= ask          (At Ask)
MID   = price between bid/ask (Mid)
BID   = price <= bid          (At Bid)
BBID  = price < bid           (Below Bid)

Buy vs Sell: Inferring Trade Direction

In options flow data, we don't have a direct "buy" or "sell" flag. Instead, we infer the likely aggressor (buyer or seller) based on where the trade executed relative to the bid-ask spread.

The Bid-Ask Spread Concept

         BID                              ASK
          │                                │
          ▼                                ▼
    ┌─────────────────────────────────────────┐
    │  Sellers willing    │   Buyers willing  │
    │  to sell at BID     │   to buy at ASK   │
    └─────────────────────────────────────────┘
                          │
                         MID

• BID price: The highest price a buyer is willing to pay
• ASK price: The lowest price a seller is willing to accept
• Spread: The difference between ASK and BID

Who is the Aggressor?

[!IMPORTANT] Key insight: The aggressor pays a premium for immediacy.

• A buyer paying ASK wants to get in NOW (urgency = conviction)
• A seller hitting BID wants to get out NOW (urgency = conviction or desperation)

Connecting to Sentiment

Once we know the likely aggressor (buyer vs seller) and the option type (CALL vs PUT), we can infer sentiment:

Sentiment Derivation (sentiment field)

The sentiment field is derived from the combination of put_call and side:

Trade Activity Types (option_activity_type field)

Quick Reference Codes

[!NOTE] These codes come from the exchange and indicate the execution mechanism. For most analysis purposes, you can focus on trade size, premium, and sentiment rather than activity type.

Trade Condition Codes

Detailed Trade Descriptions

Moneyness Classification (moneyness field)

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Foundational Concepts

Data-Driven Trading Strategy

Definition: An approach to investment using data and analytics to make informed trading decisions based on objective information rather than subjective chart interpretations.

Key Advantages:

• Uses historical data, current market conditions, and company performance
• Identifies patterns and trends not immediately apparent through technical analysis
• More reliable than technical analysis alone (less influenced by personal biases)

OptionData Application: The Smart Option Flow identifies trading opportunities when option prices deviate significantly from expected values due to unusual trading activity, providing insights into market sentiment.

Understanding Option Quotes

An option quote is not a single price, but a two-way price structure known as the NBBO (National Best Bid and Offer) that represents the market's current willingness to trade.

Components of a Quote

[!NOTE] Example Quote: Bid: $2.50 x 50 | Ask: $2.55 x 100

• Sell immediately at $2.50 (hit the bid).
• Buy immediately at $2.55 (take the ask).
• Liquidity: Market is deeper on the sell side (100 contracts) than the buy side (50 contracts).

Why Quotes Matter

1. Liquidity & Slippage: A tight spread (e.g., $0.05) indicates high liquidity. A wide spread (e.g., $0.50 on a $2.00 option) implies low liquidity, meaning you lose more value just by entering/exiting the trade.
2. Trade Inference: As explained in the Buy vs Sell section, we use the Bid/Ask prices to infer whether a trade was initiated by a buyer (Ask side) or seller (Bid side).

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Options Dictionary

Core Data Fields

Derived Metrics

Greeks (Recalculated)

[!NOTE] Greeks are recalculated locally using Black-Scholes with a 5% risk-free rate for more accurate values.

Market Concepts

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Aggregation Mode

Concept

Real-time Option Trades in AGGREGATED mode consolidates trades with the same option symbol executed simultaneously (at the second level) into a single aggregate trade. This approach simplifies the identification of large trades that have been divided into multiple smaller transactions.

RAW mode shows the original trades without any modification.

Key Differences

When to Use?

• AGGREGATED Mode (Default): In most cases, AGGREGATED Mode is sufficient. It allows you to identify significant block trades where institutional players may have divided large trades into smaller ones.
• RAW Mode: Use this mode if you specifically want to explore the unmodified, original data flow without any consolidation.

Aggregation Logic Example

Scenario: Two trades for TSLA $330 Call executed at the exact same second.

1. RAW Data Input

date        time      symbol  strike  put_call expiration_date premium size trade_count
2025-02-01  09:32:02  TSLA    330     CALL     2025-02-15       1000    2    1
2025-02-01  09:32:02  TSLA    330     CALL     2025-02-15       2000    3    1

2. AGGREGATED Output

date        time      symbol  strike  put_call expiration_date premium size trade_count
2025-02-01  09:32:02  TSLA    330     CALL     2025-02-15       3000    5    2

Calculation:

• Size: Sum of sizes (2 + 3 = 5)
• Premium: Sum of premiums (1000 + 2000 = 3000)
• Trade Count: Sum of counts (1 + 1 = 2)
• Other Fields (e.g., Delta, IV): Average of the original values.

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Unusual Options Activity (UOA)

What Is UOA?

Unusual Options Activity (UOA) refers to an abnormal surge in the volume of options contracts traded for a specific stock, compared to its average daily options volume. When options volume spikes well beyond the norm, it can indicate heightened investor interest and potential major price movements or events on the horizon.

[!IMPORTANT] An unexpected jump in call or put options on a particular stock may signal institutional activity, upcoming catalysts, or significant shifts in market sentiment.

Why Is UOA Important?

Unusual options activity provides valuable insights for traders:

Measuring UOA: Relative Volume

Relative Volume compares the current day's options trading activity to the stock's average daily options volume.

Relative Volume = Current Day's Options Volume ÷ Average Daily Options Volume

[!TIP] Focus on stocks with relative volume ≥ 2.0 to filter out normal market noise and identify truly unusual activity.

Options Volume vs. Number of Trades

It's critical to distinguish between these two metrics:

Why This Matters:

• Single Large Trade (Block Trade): Often indicates institutional activity, as large investors make substantial moves in one transaction
• Many Small Trades: Could be retail activity or market maker hedging, generally less directional signal

UOA Analysis Strategy

When analyzing unusual options activity, consider:

1. Volume Breakdown: Are calls or puts driving the volume?

   • High call volume = Bullish sentiment
   • High put volume = Bearish sentiment

2. Trade Size Distribution:

   • Large block trades = Institutional positioning
   • Scattered small trades = Less significant

3. Combined Analysis:

   • UOA + Stock price movement
   • UOA + Implied volatility changes
   • UOA + Open Interest changes (T+1 confirmation)

[!NOTE] Block Trade Threshold: Trades significantly larger than average trade size for that stock. Often indicates "smart money" positioning.

From UOA to Actionable Insights

flowchart TD
    A[Detect UOA<br/>Relative Volume ≥ 2.0] --> B{Call or Put<br/>Volume?}
    B -->|Calls| C[Bullish Signal]
    B -->|Puts| D[Bearish Signal]
    C --> E{Large Block<br/>Trades?}
    D --> E
    E -->|Yes| F[Likely Institutional<br/>High Conviction]
    E -->|No| G[Retail Activity<br/>Lower Conviction]
    F --> H[Check OI Change T+1]
    H -->|OI Increased| I[Opening Position<br/>Strong Signal]
    H -->|OI Unchanged| J[Day Trade<br/>Weaker Signal]

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Core Greeks & Metrics

Delta Exposure (DEX)

Definition

Delta: Measures how much an option's price moves when the underlying stock moves $1.

• Call options: Delta ranges from 0 to 1
• Put options: Delta ranges from -1 to 0

Delta Exposure: Translates option positions into equivalent shares.

• +500 delta exposure ≈ owning 500 shares
• -500 delta exposure ≈ shorting 500 shares

Formula (as stored in dex field)

dex = delta × size

[!IMPORTANT] Note: The stored dex field uses delta × size, not delta × size × 100. This represents delta-equivalent contracts, not shares.

Example

• Buy 10 AAPL calls at δ=0.60 → +600 delta exposure
• Sell 5 AAPL calls at δ=0.20 → -100 delta exposure
• Net: +500 delta (behaves like owning 500 shares)

Delta Trade Direction Reference

Dealer Hedging Behavior

When a trader buys an ATM call with δ=0.5, the dealer sells 50 shares to stay delta-neutral. As stock price moves, delta changes, requiring the dealer to adjust their hedge.

flowchart LR
    A[Trader Buys Call<br/>δ = 0.5] --> B[Dealer Short Call]
    B --> C[Dealer Sells 50 Shares<br/>to Hedge]
    C --> D{Stock Price Moves}
    D -->|Price ↑| E[Delta ↑<br/>Dealer Sells More]
    D -->|Price ↓| F[Delta ↓<br/>Dealer Buys Back]

Why DEX > Premium or Notional Value

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Delta Impact (DEI)

Definition

Measures how significant an option trade's directional exposure is relative to the average daily trading volume of the underlying.

Formula (as stored in dei field)

dei = dex ÷ avg_daily_volume

[!NOTE] The dei field represents the ratio of delta exposure to average daily volume, indicating the relative significance of a trade.

Interpretation

[!IMPORTANT] DEI surges often signal: institutional positioning, pre-hedging for catalysts (earnings), or anticipated volatility.

Case Study: BP Prudhoe Bay Royalty Trust ($BPT)

• Date: June 13, 2023
• DEI: 83.31% (extremely high)
• Outcome: Stock surged 6% on June 16th, up to 11% intraday
• Takeaway: Unusually high DEI preceded significant directional move

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Gamma Exposure (GEX)

Definition

Gamma: Measures how much delta changes when the underlying stock moves.

• Delta = how much option price changes when stock moves
• Gamma = how much delta changes as stock moves (the "acceleration" of delta)

Gamma Exposure: Total gamma of options positions; determines dealer hedging behavior.

flowchart TD
    subgraph "Long Gamma (Dealers Own Options)"
        A1[Market Rises] -->|Dealers Sell Stock| B1[Downward Pressure]
        A2[Market Falls] -->|Dealers Buy Stock| B2[Upward Pressure]
        B1 --> C1[**STABILIZING**<br/>Reduced Volatility]
        B2 --> C1
    end
    
    subgraph "Short Gamma (Dealers Sold Options)"
        D1[Market Rises] -->|Dealers Buy Stock| E1[More Upward Pressure]
        D2[Market Falls] -->|Dealers Sell Stock| E2[More Downward Pressure]
        E1 --> F1[**DESTABILIZING**<br/>Amplified Moves]
        E2 --> F1
    end

Gamma Environment Comparison

OptionData GEX Metrics

Call Wall vs Put Wall

These are critical GEX levels where dealers have significant gamma exposure.

Definitions

Dealer Hedging Mechanism

flowchart TD
    subgraph "Call Wall Dynamics"
        A1[Price Approaches Call Wall] --> B1[Calls Gain Delta]
        B1 --> C1[Dealers Sell Stock to Hedge]
        C1 --> D1[Downward Pressure<br/>**RESISTANCE**]
    end
    
    subgraph "Put Wall Dynamics"
        A2[Price Approaches Put Wall] --> B2[Puts Gain Delta]
        B2 --> C2[Dealers Buy Stock to Hedge]
        C2 --> D2[Upward Pressure<br/>**SUPPORT**]
    end

Comparison Table

[!NOTE] These are probabilistic indicators, not guarantees. Other factors (technicals, sentiment, fundamentals) also influence price.

Gamma Squeeze

A Gamma Squeeze is a feedback loop that forces dealers to buy stock aggressively as prices rise, causing an explosive upward move.

The Mechanism (Short Gamma)

1. Setup: Dealers are Short Gamma (they sold many OTM calls to retail/institutions).
2. Trigger: Stock price starts to rise (e.g., due to news or momentum).
3. Delta Expansion: As price rises, the delta of those short calls increases (approaches 1.0).
4. Forced Buying: To stay delta-neutral, dealers MUST buy the underlying stock.
5. Loop: Dealer buying pushes stock price higher $\to$ Deltas increase further $\to$ Dealers buy more.

flowchart TD
    A[Stock Price Rises] -->|Calls gain Delta| B["Dealers Short Calls<br/>(Must Hedge)"]
    B -->|Forced Buying| C[Dealers BUY Stock]
    C -->|Added Buying Pressure| D[Stock Price Rises Comparison]
    D -->|Feedback Loop| A
    style D fill:#f96,stroke:#333,stroke-width:2px

[!IMPORTANT] Key Warning Sign: High Call GEX combined with a rising stock price can trigger this loop. The "squeeze" ends when dealers finish hedging or the options expire/are closed.

The 0DTE Phenomenon

Definition: 0DTE (Zero Days to Expiration) options are contracts that expire at the close of the current trading day.

Significance:

• Volume Dominance: 0DTEs often account for >40% of daily volume in major indices (SPX, SPY).
• Extreme Gamma: As expiration nears, Gamma explodes, creating rapid price acceleration potential.

Market Impact: Stabilizing vs. Destabilizing

0DTE flows impact market volatility depending on dealer positioning:

Analyzing 0DTE Flow

Since OI effectively resets daily, traditional Open Interest analysis is irrelevant for 0DTE. Instead, focus on:

• Intraday Volume: Real-time surges indicate immediate positioning.
• Vanna/Charm: Second-order Greeks that decay rapidly as the closing bell approaches.

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Implied Volatility (IV)

Definition

Market's expectation of future volatility in the underlying asset's price, derived from the option's market price.

Key Factors

1. Market Sentiment: Earnings, economic data, geopolitical events
2. Time to Expiration: Longer expiration → higher IV
3. Underlying Asset: Tech stocks/commodities → higher IV than blue-chips

IV Environment Trading Guide

Volatility Patterns

Volatility Smile: IV curve that rises at both ends when plotted against strike prices (OTM puts and calls have higher IV than ATM).

Causes:

• Crash risk (OTM puts for downside protection)
• Speculation (OTM calls for upside)
• Fat-tailed distributions (extreme moves more common than models assume)

Volatility Skew: Asymmetric IV pattern common in equity markets where puts have higher IV than calls (investors fear crashes more than rallies).

IV Crush: Sharp IV decline after anticipated events (earnings, major news) as uncertainty is resolved.

[!TIP] Pre-earnings play: Consider selling premium before earnings to capture IV crush, but be aware of gap risk.

OI + IV Combined Analysis

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Option Chain Analysis

Option Chain vs Option Flow

Understanding the difference between these two data views is crucial for analysis.

The Relationship

1. Flow creates the Chain: Today's flow activity eventually settles into tomorrow's Open Interest (if trades are opening and held).
2. Chain Contextualizes Flow: A $1M call sweep is more significant if it breaks through a major "Call Wall" (Chain level) than if it happens in a vacuum.
3. Analysis Loop:
   • Watch Flow for immediate moves.
   • Check Chain to see if the move has room to run (no resistance).
   • Checks OI next day (T+1) to confirm if the Flow stuck.

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Open Interest (OI)

Definition

Total number of active option contracts that are outstanding (not yet closed, exercised, or expired).

OI vs Volume

OI Update Frequency

[!WARNING] OI is NOT Real-Time Open Interest is calculated by the OCC (Options Clearing Corporation) overnight and updated once per day before market open (approx. 6:30 AM ET).

• The OI you see during the trading day represents the previous day's closing OI.
• Intraday trades (Volume) do not update OI until the next morning.

Analyzing OI Changes & Trade Intent

Since OI is lagging, we look at the change in OI from one day to the next to determine if a large trade was "opening" (new positioning) or "closing" (liquidation).

Calculation:

ΔOI = Today's OI - Yesterday's OI

[!TIP] Example Calculation:

1. Monday: Trader buys 5,000 calls of TSLA. (Volume = 5,000)
2. Tuesday Morning:
   • If TSLA OI increased by ~5,000: The trader kept the position (Opening).
   • If TSLA OI unchanged: The trader sold before market close (Day Trade).
   • If TSLA OI decreased: The trade might have been closing an existing short position.

Why Tracking OI Change Matters

• Validates Conviction: High volume with increasing OI proves "new money" is betting on a move.
• Spots Profit Taking: High volume with decreasing OI signals that big players are exiting, potentially reversing a trend.
• Filters Noise: High volume with no OI change suggests day trading or market maker hedging, which has less long-term directional signal.

OI Change Logic Flowchart

flowchart LR
    A["Both Parties<br/>Open New Positions"] --> B["OI ↑ Increases<br/>(Opening)"]
    C["One Opens,<br/>One Closes"] --> D["OI = Unchanged<br/>(Churn)"]
    E["Both Parties<br/>Close Positions"] --> F["OI ↓ Decreases<br/>(Closing)"]

Real-Time Intraday Estimation

While we must wait for overnight updates for certainty, we can estimate intent in real-time:

[!TIP] Why assume "Opening"? In Unusual Options Activity (UOA), we typically assume aggressive trades (Ask side sweeps) are Opening positions unless proven otherwise by falling OI the next day. Institutions rarely aggressive "sweep" to exit a position; they usually exit passively to avoid slippage.

Verification (T+1)

To definitively confirm a "Likely OPENING" or "AMBIGUOUS" trade, compare the trade size to the next day's OI change (T+1 Confirmation):

[!IMPORTANT] This T+1 verification is the gold standard for separating high-conviction swing trades from intraday noise.

Why OI Matters

OptionData Opening Filter Logic

OptionData's Opening filter identifies likely new positions by filtering for trades that:

• Exceed current open interest
• Are larger than 50% of day's total volume

Formula:

(Size of Trade) > (Preceding Volume + Open Interest) = New Position