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TL;DR

A stochastic process where \( E[M_t | \mathcal{F}_s] \geq M_s \) for \( s \leq t \). It has an upward tendency on average. A supermartingale has the reverse inequality.

By Valenke Exam Prep Team·Last updated 2026-06-03

Submartingale

A stochastic process where \( E[M_t | \mathcal{F}_s] \geq M_s \) for \( s \leq t \). It has an upward tendency on average. A supermartingale has the reverse inequality.

Why it matters for interviews

Stock prices under the physical measure are typically submartingales (positive expected return). The Doob decomposition and maximal inequalities for submartingales are used in probability theory and mathematical finance.

Definition and Mathematical Foundation

A stochastic process where \( E[M_t | \mathcal{F}_s] \geq M_s \) for \( s \leq t \). It has an upward tendency on average. A supermartingale has the reverse inequality.

Application in Quantitative Finance

Stock prices under the physical measure are typically submartingales (positive expected return). The Doob decomposition and maximal inequalities for submartingales are used in probability theory and mathematical finance.

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Frequently Asked Questions

What is the Doob decomposition?
Any submartingale can be uniquely decomposed as \( M_n = X_n + A_n \) where X is a martingale and A is a predictable increasing process. This separates the 'fair' component from the systematic drift.
Why are discounted prices martingales but undiscounted prices submartingales?
Under the physical measure, assets earn a positive risk premium, making prices submartingales. Under the risk-neutral measure, assets earn the risk-free rate, and discounted prices become martingales.
What is Doob's maximal inequality?
For a non-negative submartingale: \( P(\max_{k \leq n} M_k \geq \lambda) \leq E[M_n]/\lambda \). This bounds the probability of large excursions and is used in concentration inequalities.