Trades
Log-return based metrics: variance, realized volatility, bipower variation, jump ratio, autocorrelation, and trendiness.
Need the ticks behind this metric? Prime + Raw includes raw trades.
Shown: realized_vol, hourly, 1–31 January 2024, from this page's Sample CSV · extreme: 0.420, 9 Jan, 21:00 UTC · built with returns
realized_volRealized 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_variationBipower 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_ratioJump 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_lag1Lag-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.
trendinessTrendiness 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.
/api/v1/data/returns| Field | Name | Description |
|---|---|---|
logret_var | Log-Return Variance | Variance of log returns within the interval |
realized_vol | Realized Volatility | Square root of the sum of squared log returns in the interval |
bipower_variation | Bipower Variation | Jump-robust volatility estimate built from adjacent absolute log returns |
jump_ratio | Jump Ratio | Share of realized variance not explained by bipower variation |
ret_autocorr_lag1 | Return Autocorr (Lag 1) | Lag-one autocorrelation of log returns within the interval |
trendiness | Trendiness | Absolute net log return divided by total absolute log return |
# Install the Aperiodic CLI into ~/.local/bin
mkdir -p "$HOME/.local/bin"
curl -fsSL https://raw.githubusercontent.com/aperiodic-io/cli/main/install.sh | INSTALL_DIR="$HOME/.local/bin" bash
export PATH="$HOME/.local/bin:$PATH"
# Free preview — no API key required
aperiodic returns --preview \
--exchange binance-futures \
--symbol perpetual-BTC-USDT:USDT \
--interval 5m \
--timestamp exchange \
--start-date 2025-05-01 \
--end-date 2025-05-31 \
--output-dir ./data && echo "Saved to $PWD/data"Every new row as it is computed, over WebSocket at wss://stream.aperiodic.io/v1/stream. Authenticate with your API key in the X-API-KEY header and subscribe to channels named returns.<exchange>.<interval>, on intervals 15s, 30s, 1m, 5m, 15m, 30m, 1h, 4h, 1d (15s and 30s on Institutional Live only). Streaming is included on Live plans.
pip install "aperiodic[stream]"import os
from aperiodic import stream
for message in stream(
api_key=os.environ["APERIODIC_API_KEY"],
dataset="returns",
exchange="binance-futures",
interval="1m",
symbols=["perpetual-BTC-USDT:USDT"], # omit for every symbol on your plan
):
print(message.channel, message.snapshot, message.data)timestampreqstringTimestamp source. 'exchange' uses the exchange-reported timestamp, 'true' uses actual arrival time at our servers.
exchangetrueintervalreqstringAggregation time interval for the data. Sub-minute intervals (15s, 30s) require an Institutional plan.
15s30s1m5m15m30m1h4h1dexchangereqstringSource exchange for the data.
binance-futuresokx-perpshyperliquid-perpssymbolreqstringTrading pair symbol in the format of Atlas' universal symbology: https://github.com/aperiodic-io/atlas
start_datereqstring<date>Start date for the data range (YYYY-MM-DD format). A metric series starts on the first day of the raw series it is computed from (see /metadata/raw); raw trades and quotes start binance-futures from 2020-01-01, okx-perps from 2019-09-01, hyperliquid-perps from 2025-01-01. Earlier days return no files. How far back you can go depends on the plan: 5 years on Pro, full history on Prime, Prime + Raw and Institutional. An earlier start_date than the plan reaches returns 403.
end_datereqstring<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 every existing file covering the range from the series' published start — one per month before 2026-08-01, one per day from 2026-08-01 onwards
filesobject[]requiredFiles covering the requested date range, in chronological order. Data before 2026-08-01 is split by month (one file per calendar month, no `day`); data from 2026-08-01 onwards is split by day (one file per calendar day, with `day` set). The changeover falls on a month boundary, so a given month is served entirely one way or the other; a range spanning it returns the earlier months as monthly files followed by a daily file per day.
yearintegerrequiredYear of the data file
monthintegerrequiredMonth of the data file (1-12)
dayintegerDay of the data file (1-31). Present only on daily files, i.e. those covering 2026-08-01 onwards. Absent on monthly files, which cover an entire calendar month.
urlstring<uri>requiredPresigned 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.
{
"files": [
{
"year": 2026,
"month": 6,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-06.parquet?X-Amz-Expires=300&..."
},
{
"year": 2026,
"month": 7,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-07.parquet?X-Amz-Expires=300&..."
},
{
"year": 2026,
"month": 8,
"day": 1,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-01.parquet?X-Amz-Expires=300&..."
},
{
"year": 2026,
"month": 8,
"day": 2,
"url": "https://ohlcv.aperiodic.io/binance-futures/1h/BTCUSDT/2026-08-02.parquet?X-Amz-Expires=300&..."
}
]
}
Prefilled with the shared DEMO-KEY and a free preview slice — send the request to see live data, no account required.
/api/v1/data/preview/returns?timestamp=exchange&interval=5m&exchange=binance-futures&symbol=perpetual-BTC-USDT%3AUSDT&start_date=2025-05-01&end_date=2025-05-31Access a curated slice of real production data with just an account — no credit card or subscription required. Pair it with our research notebooks to get started instantly.