Paper: arXiv 2502.18625

Abstract

Using data from a live trading experiment on the Binance Bitcoin perpetual, we examine the effects of (i) basic order book mechanics and (ii) the persistence of price changes from immediate to short timescales, revealing the interplay between returns, queue sizes, and orders’ queue positions. We document a fundamental trade-off: a negative correlation between maker fill likelihood and post-fill returns. This dictates that viable maker strategies often require a contrarian approach, counter-trading the prevailing order book imbalance. These dynamics render commonly-cited strategies highly unprofitable, leading us to model `Reversals’: situations where a contrarian maker strategy at the touch proves effective.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 8.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper uses stochastic modeling and queueing theory (advanced math) but grounds it in a live trading experiment with real data and implementation details.

Research Flowchart

  flowchart TD
  Start["Research Goal: Uncover the trade-off between fill probability & post-fill returns for market makers using live data"] --> Data
  subgraph Data["Data/Inputs"]
      Binance["Live Trading Experiment Data<br/>(Binance BTC Perpetual)"]
  end
  Data --> Process
  subgraph Process["Computational Analysis"]
      E1["(i) Analyze Basic Order Book Mechanics<br/>(Queue Size, Positions)"]
      E2["(ii) Analyze Price Change Persistence<br/>(Immediate to Short Timescales)"]
      E1 --> Int["Identify Interplay:<br/>Returns vs. Queue Positions vs. Fill Likelihood"]
      E2 --> Int
  end
  Process --> Find
  subgraph Find["Key Findings/Outcomes"]
      Trade["Documented Trade-off:<br/>Negative Correlation<br/>Fill Probability ↗ & Post-Fill Returns ↘"]
      Strat["Strategy Implication:<br/>Viable Maker Strategies require Contrarian Approach<br/>(Counter-trade order book imbalance)"]
      Rev["Model 'Reversals':<br/>Situations where contrarian maker strategy at the touch is effective"]
  end

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and 55 more
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  3. How and When are High-Frequency Stock Returns Predictable? (2022) — link
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0 of 63 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.