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Survival Models for the Duration of Bid-Ask Spread Deviations

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arxiv 1406.5487 v1 pith:TNLZ7QJN submitted 2014-06-20 q-fin.ST

classification q-fin.ST
keywords liquiditydeviationsdurationmanymodelspreadsurvivalalgorithm
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Many commonly used liquidity measures are based on snapshots of the state of the limit order book (LOB) and can thus only provide information about instantaneous liquidity, and not regarding the local liquidity regime. However, trading in the LOB is characterised by many intra-day liquidity shocks, where the LOB generally recovers after a short period of time. In this paper, we capture this dynamic aspect of liquidity using a survival regression framework, where the variable of interest is the duration of the deviations of the spread from a pre-specified level. We explore a large number of model structures using a branch-and-bound subset selection algorithm and illustrate the explanatory performance of our model.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When Does Order Flow Matter? State-Dependent L2 Liquidity-State Transitions in Crypto Futures

    q-fin.TR 2026-07 conditional novelty 6.0 of 10

    In Binance BTC/ETH futures event windows, pre-event L2 liquidity state dominates post-event regime prediction; order flow helps only as an ETH-dominant, stress-amplified overlay.

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