Hedging in Sequential Experiments
Thomas Cook, Patrick Flaherty

TL;DR
This paper introduces a game-theoretic framework for experimentalists to hedge against the risk of null results and false positives, using financial and portfolio theories to manage experimental uncertainty.
Contribution
It develops a novel method to hedge experimental risk by capitalizing test martingales and constructing derivative instruments within a game-theoretic setting.
Findings
Test martingale wealth can be priced using risk-neutral valuation.
A portfolio combining risky and risk-free assets remains a test martingale.
Hedging instruments can be derived from the test martingale process.
Abstract
Experimentation involves risk. The investigator expends time and money in the pursuit of data that supports a hypothesis. In the end, the investigator may find that all of these costs were for naught and the data fail to reject the null. Furthermore, the investigator may not be able to test other hypotheses with the same data set in order to avoid false positives due to p-hacking. Therefore, there is a need for a mechanism for investigators to hedge the risk of financial and statistical bankruptcy in the business of experimentation. In this work, we build on the game-theoretic statistics framework to enable an investigator to hedge their bets against the null hypothesis and thus avoid ruin. First, we describe a method by which the investigator's test martingale wealth process can be capitalized by solving for the risk-neutral price. Then, we show that a portfolio that comprises the…
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Taxonomy
TopicsAdvanced Statistical Process Monitoring
MethodsSparse Evolutionary Training
