--- title: "Martingale" firstLetter: "M" publishDate: 2021-10-31 categories: - Mathematics date: 2021-10-18T10:01:46+02:00 draft: false markup: pandoc --- # Martingale A **martingale** is a type of stochastic process (i.e. a time-indexed [random variable](/know/concept/random-variable/)) with important and useful properties, especially for stochastic calculus. For a stochastic process $\{ M_t : t \ge 0 \}$ on a probability space $(\Omega, \mathcal{F}, P)$ with filtration $\{ \mathcal{F}_t \}$ (see [$\sigma$-algebra](/know/concept/sigma-algebra/)), then $\{ M_t \}$ is a martingale if it satisfies all of the following: 1. $M_t$ is $\mathcal{F}_t$-adapted, meaning the filtration $\mathcal{F}_t$ contains enough information to reconstruct the current and all past values of $M_t$. 2. For all times $t \ge 0$, the expectation value exists $\mathbf{E}(M_t) < \infty$. 3. For all $s, t$ satisfying $0 \le s \le t$, the [conditional expectation](/know/concept/conditional-expectation/) $\mathbf{E}(M_t | \mathcal{F}_s) = M_s$, meaning the increment $M_t \!-\! M_s$ is always expected to be zero $\mathbf{E}(M_t \!-\! M_s | \mathcal{F}_s) = 0$. The last condition is called the **martingale property**, and essentially means that a martingale is an unbiased random walk. Accordingly, the [Wiener process](/know/concept/wiener-process/) $\{ B_t \}$ (Brownian motion) is a prime example of a martingale (with respect to its own filtration), since each of its increments $B_t \!-\! B_s$ has mean $0$ by definition. Modifying property (3) leads to two common generalizations. The stochastic process $\{ M_t \}$ above is a **submartingale** if the current value is a lower bound for the expectation: 3. For $0 \le s \le t$, the conditional expectation $\mathbf{E}(M_t | \mathcal{F}_s) \ge M_s$. Analogouly, $\{ M_t \}$ is a **supermartingale** if the current value is an upper bound instead: 3. For $0 \le s \le t$, the conditional expectation $\mathbf{E}(M_t | \mathcal{F}_s) \le M_s$. Clearly, submartingales and supermartingales are *biased* random walks, since they will tend to increase and decrease with time, respectively. ## References 1. U.H. Thygesen, *Lecture notes on diffusions and stochastic differential equations*, 2021, Polyteknisk Kompendie.