Detecting Intraday Anomalies in European Crypto Exchange-Traded Products

Summary

This study examines intraday anomalies in Bitcoin and Ethereum exchange-traded products listed on Xetra and Nasdaq Stockholm, using one-minute bars from January 2024 through December 2025. Its benchmark identifies extreme negative returns by fitting a generalized Pareto distribution to left-tail exceedances. The authors add three binary indicators: price divergence across venues, extreme drops with little recovery over the next ten active bars, and extreme drops that follow positive short-term momentum.

Each anomaly category accounts for fewer than 1% of bars. Mann-Whitney U tests find that anomalous observations have higher effective spreads, liquidity-related ratios, and order-flow imbalances than ordinary bars. Four classifiers predict anomalies one bar ahead, with reported AUC-ROC values up to 0.82; permutation importance favors short-term volatility and drawdown measures over microstructure variables in general. These findings concern anomaly classification and associated market conditions, not a tested trading strategy. The excerpt gives no details about trading costs or whether acting on predictions would be profitable, and the results are limited to the specified products, venues, period, and bar frequency.

Key ideas

• A generalized Pareto distribution is used to flag extreme negative return bars as a benchmark.
• Three additional indicators capture cross-venue divergence, lack of recovery, and reversals after positive momentum.
• Anomalous bars are associated with wider effective spreads and stronger liquidity ratios and order-flow imbalances.
• Four classifiers show one-bar-ahead predictability, with AUC-ROC values up to 0.82.
• Short-term volatility and drawdown measures are generally more useful predictors than microstructure variables.

Tags

# Anomaly detection in European cryptocurrency exchange-traded products


# Anomaly detection in European cryptocurrency exchange-traded products









Cryptocurrency exchange-traded products (ETPs) listed on European exchanges provide a regulated environment for studying intraday market anomalies. We study four Bitcoin and Ethereum ETPs traded on Xetra and Nasdaq Stockholm over the period January 2024 - December 2025 using one-minute bars. As a benchmark, we adopt an extreme value theory approach in which anomalous bars are defined as returns falling below a threshold estimated by fitting a generalised Pareto distribution to left-tail exceedances. We then propose three new binary anomaly indicators. The first, a cross-venue divergence anomaly, identifies venue-specific price divergence between the two exchanges. The second is a no-recovery anomaly that identifies extreme price drops followed by little or no recovery over the next ten active bars. The third is a momentum-reversal anomaly that identifies extreme price drops following positive short-term momentum. Although each anomaly type represents fewer than 1% of one-minute bars, statistical analysis using Mann-Whitney U tests shows that anomaly observations exhibit significantly higher effective spreads, higher values of liquidity-related ratios, and more pronounced order-flow imbalances than non-anomalous bars. Furthermore, employing an out-of-sample prediction methodology with four classifiers - random forest, logistic regression, extreme gradient boosting, and light gradient boosting machine - shows that all four anomaly types are predictable one bar ahead, with AUC-ROC values of up to 0.82. Permutation importance indicates that short-term volatility and drawdown measures are generally more useful for prediction than microstructure variables.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.