A New Application of Hoeffding's Inequality Can Give Traders Early Warning of Financial Regime Change

Daniel Egger and Jacob Vestal

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Abstract: Hoeffding's Inequality provides the maximum probability that a series of n draws from a bounded random variable differ from the variable's true expectation u by more than given tolerance t. The random variable is typically the error rate of a classifier in machine learning applications. Here, a trading strategy is premised on the assumption of an underlying distribution of causal factors, in other words, a market regime, and the random variable is the performance of that trading strategy. A larger deviation of observed performance from the trader's expectation u can be characterized as a lower probability that the financial regime supporting that strategy remains in force, and a higher probability of financial regime change. The changing Hoeffding probabilities can be used as an early warning indicator of this change.

Date: 2025-12
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