Paper: arXiv 2602.19590

Authors: Ezra Goliath, Tim Gebbie

Abstract

Market-order flow in financial markets exhibits long-range correlations. This is a widely known stylised fact of financial markets. A popular hypothesis for this stylised fact comes from the Lillo-Mike-Farmer (LMF) order-splitting theory. However, quantitative tests of this theory have historically relied on proprietary datasets with trader identifiers, limiting reproducibility and cross-market validation. We show that the LMF theory can be validated using publicly available Johannesburg Stock Exchange (JSE) data by leveraging recently developed methods for reconstructing synthetic metaorders. We demonstrate the validation using 3 years of Transaction and Quote Data (TAQ) for the largest 100 stocks on the JSE when assuming that there are either N=50 or N=150 effective traders managing metaorders in the market.

Complexity vs Empirical Score

  • Math Complexity: 5.5/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides a compelling empirical validation of the Lillo-Mike-Farmer (LMF) order-splitting theory using synthetic metaorders reconstructed from public JSE market data. It bridges theoretical market microstructure (power laws, autocorrelation) with practical computational techniques, demonstrating high empirical utility and clear algorithmic explanations.

Research Flowchart

  flowchart TD
    A["Research Goal: Validate LMF Order-Splitting Theory via Public Data"] --> B["Input Data: 3 Years JSE TAQ Data (Top 100 Equities)"]
    B --> C["Apply Synthetic Metaorder Reconstruction Methods"]
    C --> D["Parameter Modeling: Set Effective Traders (N=50 and N=150)"]
    D --> E["Analyze Market-Order Flow Long-Range Correlations"]
    E --> F["Outcome: Successfully Validated LMF Theory Using Public Data"]

Cited References (23)

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and 15 more
  1. Beyond the square root: Evidence for logarithmic dependence of market impact on size and participation rate (2014) — link
  2. Quantitative statistical analysis of order-splitting behavior of individual trading accounts in the Japanese stock market over nine years (2023) — link
  3. Inferring Microscopic Financial Information from the Long Memory in Market-Order Flow: A Quantitative Test of the Lillo-Mike-Farmer Model (2023) — link
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0 of 23 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.