VRP History API

Endpoint

GET /v1/vrp/{symbol}/history

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

Parameters

Name	In	Required	Default	Description
`symbol`	path	yes	-	Stock/ETF ticker
`days`	query	no	30	Lookback days (1-365)

curl -H "X-Api-Key: YOUR_API_KEY" \
  "https://lab.flashalpha.com/v1/vrp/SPY/history?days=30"

import requests

resp = requests.get(
    "https://lab.flashalpha.com/v1/vrp/SPY/history",
    headers={"X-Api-Key": "YOUR_API_KEY"},
    params={"days": 30}
)
data = resp.json()
print(f"Data points: {data['data_points']}")

const resp = await fetch(
  "https://lab.flashalpha.com/v1/vrp/SPY/history?days=30",
  { headers: { "X-Api-Key": "YOUR_API_KEY" } }
);
const data = await resp.json();
console.log("Data points: " + data.data_points);

API Key

Response

{
  "symbol": "SPY",
  "days": 30,
  "data_points": 22,
  "history": [
    {
      "date": "2026-05-30",
      "spot": 531.55,
      "atm_iv": 13.4,
      "rv_5d": 9.8,
      "rv_30d": 11.2,
      "vrp_20d": 2.2,
      "straddle": 6.85,
      "expected_move_1d": 4.32
    }
  ]
}

Key Response Fields

Field	Type	Description
`symbol`	string	Ticker symbol
`days`	number	Requested lookback
`data_points`	number	Number of data points returned
`history[].date`	date	Snapshot date
`history[].spot`	number	Close price
`history[].atm_iv`	number?	ATM IV (%)
`history[].rv_5d` ... `rv_30d`	number?	Realized vol windows
`history[].vrp_20d`	number?	VRP spread (ATM_IV - RV20d)
`history[].straddle`	number?	ATM straddle price ($)
`history[].expected_move_1d`	number?	1-day expected move ($)

Errors

Status	Description
`403`	Requires Alpha plan or higher

About

VRP History returns a daily volatility risk premium time series for charting and backtesting. Each row pairs the close price with ATM IV, realized vol windows, the 20-day VRP spread (ATM_IV minus RV20d), ATM straddle price, and the 1-day expected move. The series is populated by the nightly data service after market close (4:35 PM ET).

ATM IV is computed via BSM from Thetadata option snapshots, independent of real-time pollers. Realized vol comes from Yahoo Finance historical closes using log returns and sample standard deviation. Z-score and percentile metrics become available after 5 or more data points have accumulated.

Common Use Cases

Chart the implied-versus-realized spread over time by plotting history[].atm_iv against the rv_5d...rv_30d windows per symbol
Backtest short-vol or long-vol entries against historical vrp_20d to measure the edge of selling when the spread is wide
Score expected-move accuracy by comparing expected_move_1d to the next day's realized close-to-close move
Build percentile or z-score overlays from the vrp_20d series once 5+ data_points exist, defining rich/cheap thresholds with no lookahead bias
Calibrate straddle pricing by tracking history[].straddle versus realized range to size premium-selling positions
Detect regime shifts where vrp_20d compresses or flips negative, flagging when realized vol is overtaking implied

Complementary endpoints

VRP - the live VRP dashboard with z-score, percentile, and dealer risk
Realized Volatility - the RV windows that anchor the spread
VIX State - index-level vol regime context for the time series