BJF Trading Group Facebook ad: “Quantifying the Execution-Time Gap in Latency Arbitrage…”

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📄 New open-access academic paper on Zenodo A new academic paper has just been published in open-access form on Zenodo, the CERN-operated research repository. Title: Quantifying the Execution-Time Gap in Latency Arbitrage Backtests: A Mathematical Framework with Empirical Validation Author: Boris Fesenko, BJF Trading Group Inc. DOI: https://doi.org/10.5281/zenodo.20616790 The paper formalizes a question that every algorithmic strategy designer eventually asks, but few backtests address explicitly: how much of the simulated edge survives once production execution latency is taken into account. Three within-window decay regimes (step, linear, exponential) and three opportunity-duration distributions (exponential, uniform, log-normal) are combined into nine analytical cases. For each, a closed-form expression for the retention ratio is derived. The framework is empirically validated against a Monte Carlo simulation calibrated to a published broker-execution dataset, with closed-form predictions matching simulated outcomes to within Monte Carlo statistical error bounds. A worked numerical example from the paper: a backtest edge of 0.7 pips per opportunity, a log-normal window with a median of 94 milliseconds, and a round-trip time of 200 milliseconds under linear decay together yield a production edge of 0.091 pips. Roughly 87 percent of the backtest edge is gone before the trader can capture it. The framework makes this calculation reproducible from measurable broker-level inputs. The paper runs to 15 pages with full proofs in the appendix and an open-access reproducibility supplement (LaTeX source and bibliography file) included on the Zenodo record. Licensed CC-BY 4.0. Read the paper: https://doi.org/10.5281/zenodo.20616790 Companion site page covering the practical broker-execution angle: https://bjftradinggroup.com/latency-arbitrage-backtest-execution-time-gap/

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Quantifying the Execution-Time Gap in Latency Arbitrage Backtests: A Mathematical Framework with Empirical Validation

Latency arbitrage backtests for retail foreign exchange and cryptocurrency markets routinely assume zero-latency order fills, so the simulated edge per opportunity matches the price differential observed at the moment of signal. Production execution introduces a deterministic round-trip time T betwe...