Test Martingales for bounded random variables
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Abstract (arXiv)
Given a random sample from a random variable T which is bounded from above, T≤τ a.s., we define processes that are positive supermartingales if E(T)≥μ. Such processes are called test martingales. Tests of the supermartingale hypothesis implicitly test the hypothesis H0:E(T)≥μ. We construct test martingales that lead to tests with power 1. We also construct confidence upper bounds. We extend the techniques to testing H0:E(T)=μ and constructing confidence intervals. In financial auditing random sampling is proposed as one of the possible techniques to gather enough assurance to be able to state that there is no 'material' misstatement in a financial report. The goal of our work is to provide a mathematical context that could represent such process of gathering assurance by means of repeated random sampling.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jan 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 1; 2026: 3.
5 papers.
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- 2026Always-On Experimentation30 Sep 2026
- 2026Correcting Split Selection in Online Decision Trees via Anytime-Valid Inference29 May 2026
- 2026Multi-Armed Sequential Hypothesis Testing by Betting18 Mar 2026
- 2025STaR-Bets: Sequential Target-Recalculating Bets for Tighter Confidence Intervals28 May 2025
- 2021Tight Concentrations and Confidence Sequences from the Regret of Universal Portfolio27 Oct 2021