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Returns & Volatility

Log-return based metrics: variance, realized volatility, bipower variation, jump ratio, autocorrelation, and trendiness.

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realized_vol

Realized Volatility

Realized Volatility aggregates squared log returns into a direct estimate of how much the market actually moved during the interval.

It is one of the core building blocks for short-horizon risk, execution timing, and market-state classification.

bipower_variation

Bipower Variation

Bipower Variation is a jump-robust volatility estimator that emphasizes the continuous part of price variation.

By filtering the influence of outsized moves, it helps distinguish routine trading noise from intervals dominated by discrete jumps.

jump_ratio

Jump Ratio

Jump Ratio estimates how much of realized variance came from jump-like moves rather than from continuous fluctuations.

When it spikes, the interval was driven less by gradual repricing and more by abrupt discontinuities.

ret_autocorr_lag1

Return Autocorr (Lag 1)

Lag-1 return autocorrelation tells you whether successive micro-returns tended to continue or reverse.

Positive readings suggest short-horizon persistence, while negative readings hint at mean reversion and bounce-back behavior.

trendiness

Trendiness

Trendiness compares the net signed move to the total absolute movement inside the interval.

Values near one indicate that most movement lined up in the same direction, while values near zero imply a lot of back-and-forth cancellation.

Does price tend to continue or reverse? This is the most consequential question for any directional strategy. Rather than inferring the answer from backtests of momentum strategies (which conflate the signal with execution, risk management, and survivorship), you can measure it directly from the return series.

Endpoint

/api/v1/data/returns

Category

Trades

Intervals
1m5m15m30m1h4h1d
Requires Prime
1s

Requires timestamp=true

Exchanges
binance-futuresokx-perpshyperliquid-perps
Fields6
logret_varLog-Return VarianceVariance of log returns within the interval
realized_volRealized VolatilitySquare root of the sum of squared log returns in the interval
bipower_variationBipower VariationJump-robust volatility estimate built from adjacent absolute log returns
jump_ratioJump RatioShare of realized variance not explained by bipower variation
ret_autocorr_lag1Return Autocorr (Lag 1)Lag-one autocorrelation of log returns within the interval
trendinessTrendinessAbsolute net log return divided by total absolute log return
Example Request
from datetime import date
from aperiodic import get_metrics
df = get_metrics(
    api_key="YOUR_API_KEY",
    metric="returns",
    exchange="binance-futures",
    symbol="perpetual-BTC-USDT:USDT",
    interval="1d",
    start_date=date(2024, 1, 1),
    end_date=date(2024, 3, 1),
)
print(df.head())

Query Parameters

timestampreqstring
string

Timestamp source. 'exchange' uses the exchange-reported timestamp, 'true' uses actual arrival time at our servers.

exchangetrue
intervalreqstring
string

Aggregation time interval for the data.

1m5m15m30m1h4h1d
exchangereqstring
string

Source exchange for the data.

binance-futuresokx-perpshyperliquid-perps
symbolreqstring
string

Trading pair symbol in the format of Atlas' universal symbology: https://github.com/aperiodic-io/atlas

start_datereqstring<date>
string<date>

Start date for the data range (YYYY-MM-DD format). Data is partitioned by year and month.

end_datereqstring<date>
string<date>

End date for the data range (YYYY-MM-DD format). Must be greater than or equal to start_date.

Successful response with download URLs for each monthly file

Schema
filesobject[]required

Array of file information for each month in the requested date range

yearintegerrequired

Year of the data file

monthintegerrequired

Month of the data file (1-12)

urlstring<uri>required

Presigned URL for direct file download (valid for 5 minutes). URLs are served from dataset-specific subdomains, e.g. ohlcv.aperiodic.io, trade-metrics.aperiodic.io, l1-metrics.aperiodic.io, l2-metrics.aperiodic.io, derivative-metrics.aperiodic.io.

Example
{
  "files": [
    {
      "year": 2024,
      "month": 1,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2024-01.parquet?X-Amz-Expires=300&..."
    },
    {
      "year": 2024,
      "month": 2,
      "url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2024-02.parquet?X-Amz-Expires=300&..."
    }
  ]
}
Try It
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Suggestions shown — any valid value accepted
Authentication
Sign up to query preview data — no subscription needed.Create account
GET/api/v1/data/returns?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT%3AUSDT&start_date=2025-05-01&end_date=2025-05-31
Response will appear here

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