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Runnable research notebook

Alpha Discovery Walkthrough

Follow the full path from raw order flow to a ranked, backtestable alpha signal — every step in real, runnable code.

Built on Aperiodic's point-in-time microstructure, liquidity and flow metrics, pulled as parquet files via API or CLI.

Below are pre-executed results. Run it yourself free on preview data — no subscription — or use the CLI with DEMO-KEY.

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Other notebooks

More runnable research notebooks built on Aperiodic metrics. View the pre-executed results, then run them yourself on preview data.

Intro to Aperiodic Derivatives Metrics

This notebook introduces a simple derivatives regime dashboard using Aperiodic's `funding`, `open_interest`, and `basis` metrics for Binance BTC perpetuals over September 1, 2025 → February 28, 2026 at 5-minute frequency.

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Intro to Aperiodic Flow Metrics

This notebook introduces order-flow analytics with the `aperiodic` Python package. We focus on a single large-cap instrument — Binance BTC perpetuals (`perpetual-BTC-USDT:USDT`) — over the exact six-month window from September 1, 2025 through February 28, 2026, using 1-hour observations.

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Intro to Aperiodic L1 Price Metrics

This notebook explores top-of-book (L1) pricing with Aperiodic's `l1_price` metric for Binance BTC perpetuals from September 1, 2025 through February 28, 2026 at 5-minute granularity.

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Predicting Short-Term Crypto Returns with Market Microstructure

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