q-fin.CP · 2026-08-16 · No. 86

Computational Finance, 2026-08-16.

1 new papers in q-fin.CP. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    LOB-ID: Evaluating Synthetic Market Data by Inception Distances

    Andreea Bacalum, Zhuohan Wang, Ollie Olby, Martin Garaj, Namid Stillman

    q-fin.CP · cs.AI · cs.CE

    Generative models of limit orderbook (LOB) data have advanced rapidly, but their evaluation often focuses on stylised facts and selected market statistics. These measures provide useful diagnostics but may not capture the joint temporal and cross-level structure of order-book trajectories. We introduce LOB-ID, an embedding-based framework that adapts the Fréchet Inception Distance (FID) and Monge Inception Distance (MIND) to LOB data. To...

    arxiv.org/abs/2608.13082 · PDF

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