Works with CME index futures. Pass ES=F or NQ=F and URL-encode the = as %3D - e.g. /v1/exposure/narrative/ES%3DF. Options-on-futures are priced with Black-76 using the CME multiplier ($50/pt ES, $20/pt NQ); CME index futures are Growth-tier. See the futures hub.

Endpoint

GET /v1/exposure/narrative/{symbol}

Auth required (X-Api-Key) Rate Limited: Yes Growth plan+

Parameters

Name	In	Required	Default	Description
`symbol`	path	yes	-	Underlying symbol

curl -H "X-Api-Key: YOUR_API_KEY" \
  "https://lab.flashalpha.com/v1/exposure/narrative/SPY"

import requests

resp = requests.get(
    "https://lab.flashalpha.com/v1/exposure/narrative/SPY",
    headers={"X-Api-Key": "YOUR_API_KEY"}
)
data = resp.json()
print(data['narrative']['regime'])
print(data['narrative']['outlook'])

const resp = await fetch(
  "https://lab.flashalpha.com/v1/exposure/narrative/SPY",
  { headers: { "X-Api-Key": "YOUR_API_KEY" } }
);
const data = await resp.json();
console.log(data.narrative.regime);
console.log(data.narrative.outlook);

API Key

Response

{
  "symbol": "SPY",
  "underlying_price": 597.505,
  "as_of": "2026-02-28T16:30:45Z",
  "narrative": {
    "regime": "Dealers are long gamma (net GEX +$2.9B)  -  expect mean-reverting, range-bound price action.",
    "gex_change": "Net GEX increased from +$2.6B to +$2.9B (+11.5%)  -  gamma cushion strengthening.",
    "key_levels": "Call wall at 600, Put wall at 595, Gamma flip at 595.25.",
    "flow": "Top OI changes: +5,000 call OI at 600 strike, -2,000 put OI at 595 strike.",
    "vanna": "Positive vanna (+$1.2B) with VIX at 18.5  -  vol compression supports upside.",
    "charm": "Positive charm (+$850M)  -  time decay pushing dealers to buy, providing support.",
    "zero_dte": "0DTE accounts for 10% of total GEX  -  minimal intraday impact.",
    "outlook": "Positive gamma regime with strengthening cushion. Testing 600 call wall.",
    "data": {
      "net_gex": 2850000000,
      "net_gex_prior": 2600000000,
      "net_gex_change_pct": 9.6,
      "vix": 18.5,
      "gamma_flip": 595.25,
      "call_wall": 600.0,
      "put_wall": 595.0,
      "regime": "positive_gamma",
      "zero_dte_pct": 10.0,
      "top_oi_changes": [{"strike": 600.0, "type": "C", "oi_change": 5000, "volume": 1250}]
    }
  }
}

Key Response Fields

Field	Type	Description
`symbol`	string	Underlying symbol
`underlying_price`	number	Current price of underlying
`as_of`	string	ISO 8601 timestamp
`narrative.regime`	string	Plain-English gamma regime description
`narrative.gex_change`	string	Day-over-day GEX change narrative
`narrative.key_levels`	string	Key price levels summary
`narrative.flow`	string	Notable options flow activity
`narrative.vanna`	string	Vanna exposure interpretation
`narrative.charm`	string	Charm exposure interpretation
`narrative.zero_dte`	string	0DTE impact assessment
`narrative.outlook`	string	Overall market outlook summary
`narrative.data`	object	Raw numeric data backing each narrative section

What Is Narrative Analysis?

The Narrative endpoint translates raw options exposure data into a structured, plain-English market briefing. Instead of interpreting numbers yourself, you get ready-to-use sections covering the gamma regime, day-over-day GEX changes, key price levels, notable flow activity, vanna and charm effects, 0DTE significance, and an overall outlook. The response also includes the raw numeric data backing each narrative section, so you can combine human-readable text with quantitative analysis.

Common Use Cases

Auto-generate morning briefings - concatenate narrative.regime, key_levels, and outlook into a pre-market report without hand-interpreting numbers
Drop into client research - paste the narrative.* sections straight into newsletters or client-facing notes as finished prose
Feed chat assistants - pipe narrative.outlook and narrative.flow into a trading chatbot so it answers in plain English
Enrich alerts with context - attach narrative.gex_change to an exposure alert so recipients see why the move matters
Combine text with raw numbers - render the prose to humans while routing narrative.data (net_gex, vix, call_wall, put_wall) to your quant logic
Score qualitative signals - map narrative.regime to a directional bias and backtest it alongside quantitative indicators

Complementary endpoints

Exposure Summary - the structured numbers behind the narrative prose
Key Levels - the exact gamma flip, call wall, and put wall the narrative references
Gamma Exposure (GEX) - the per-strike detail behind the regime narrative
Flow Summary - quantify the flow activity the narrative calls out

Narrative Analysis API