Where Price Goes Is Not How to Profit: Testing "Liquidity Magnet" Price Levels in Bitcoin Perpetual Futures

Traders often treat prior highs and lows as "magnets" that attract price. Using 2.1 million one-minute Bybit BTCUSDT candles (2021-2024), this paper tests the idea as a destination forecast and as a source of trades. The nearer of two candidate levels was reached first in 71.9% of 7,085 events, against 70.5% predicted by a driftless first-passage model using distance alone. An exact-distance mirror placebo on the same price paths left a 2.2 percentage-point residual, larger at previous-day highs and lows, but the effect was unstable across years, absent in trending conditions, and did not improve walk-forward out-of-sample forecasts over distance alone. No entry design converted the forecast into profit: the best earned 8.3 basis points per trade before costs, below a round-trip cost of about 13 basis points, and simple non-magnet confirmation placebos performed as well. Independent reconstructions and a machine-learning extension to ETH and XRP reached the same conclusion.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-04
DOI
https://doi.org/10.5281/zenodo.23965420
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
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article

Where Price Goes Is Not How to Profit: Testing "Liquidity Magnet" Price Levels in Bitcoin Perpetual Futures

Rayan Tariq
Zenodo (CERN European Organization for Nuclear Research)
Financial Markets and Investment Strategies
article

Where Price Goes Is Not How to Profit: Testing "Liquidity Magnet" Price Levels in Bitcoin Perpetual Futures

Rayan Tariq
article en

Abstract

Traders often treat prior highs and lows as "magnets" that attract price. Using 2.1 million one-minute Bybit BTCUSDT candles (2021-2024), this paper tests the idea as a destination forecast and as a source of trades. The nearer of two candidate levels was reached first in 71.9% of 7,085 events, against 70.5% predicted by a driftless first-passage model using distance alone. An exact-distance mirror placebo on the same price paths left a 2.2 percentage-point residual, larger at previous-day highs and lows, but the effect was unstable across years, absent in trending conditions, and did not improve walk-forward out-of-sample forecasts over distance alone. No entry design converted the forecast into profit: the best earned 8.3 basis points per trade before costs, below a round-trip cost of about 13 basis points, and simple non-magnet confirmation placebos performed as well. Independent reconstructions and a machine-learning extension to ETH and XRP reached the same conclusion.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 12%
Financial Markets and Investment Strategies
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