Journal article
The good, the bad, and latency: exploratory trading on Bybit and Binance
- Abstract:
- We present the findings of a large-scale live trading experiment involving the placement of millions of market orders sent at a high frequency on two cryptocurrency exchanges, Bybit and Binance. We analyze the execution outcomes of these orders in comparison to the expected outcome based on the most recent snapshot of the Limit Order Book (LOB) at the time of order submission for two execution modes: one using market orders and the second using marketable limit orders aiming at the best price. Discrepancies between the actual and expected outcomes are due to intermittent LOB updates during a time span resulting from delays on the exchange, delays on the trader's end, or communication delays between the trader and the exchange. We show these discrepancies are strongly correlated with market factors such as volatility, latency, and LOB liquidity. Notably, we find a consistent disadvantage to the trader, pointing to an adverse selection effect for taker orders: profitable orders (as measured by short-term future PnL returns) tend to achieve worse-than-expected outcomes, while unprofitable orders typically achieve their expected (adverse) outcomes. In the case of market orders, this translates to a worsening of fill prices, while marketable limit orders suffer from a substantial probability of failing-to-fill-immediately. Quantitative researchers who fail to take these effects into account face the familiar litany of underperforming in a live trading environment relative to stellar backtests. To address this concern, we propose parsimonious models to estimate an order's probability of failing-to-fill-immediately (in case of a marketable limit order) and the worsening of its fill price (in case of a market order), allowing for greater accuracy when carrying out backtests and minimizing the discrepancy between backtest and realized live PnL.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.7MB, Terms of use)
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- Publisher copy:
- 10.1080/14697688.2025.2515933
Authors
- Publisher:
- Taylor & Francis
- Journal:
- Quantitative Finance More from this journal
- Volume:
- 25
- Issue:
- 6
- Pages:
- 919–947
- Publication date:
- 2025-06-24
- Acceptance date:
- 2025-05-29
- DOI:
- EISSN:
-
1469-7696
- ISSN:
-
1469-7688
- Language:
-
English
- Keywords:
- Pubs id:
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2126876
- Local pid:
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pubs:2126876
- Deposit date:
-
2025-05-27
- ARK identifier:
Terms of use
- Copyright holder:
- Albers et al
- Copyright date:
- 2025
- Rights statement:
- © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed,or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
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