Tanaka's formula

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In the stochastic calculus, Tanaka's formula states that

|B_t| = \int_0^t \sgn(B_s)\, dB_s + L_t

where Bt is the standard Brownian motion, sgn denotes the sign function

\sgn (x) = \begin{cases} +1, & x > 0; \\0,& x=0  \\-1, & x < 0. \end{cases}

and Lt is its local time at 0 (the local time spent by B at 0 before time t) given by the L2-limit

L_{t} = \lim_{\varepsilon \downarrow 0} \frac1{2 \varepsilon} | \{ s \in [0, t] | B_{s} \in (- \varepsilon, + \varepsilon) \} |.


Tanaka's formula is the explicit Doob–Meyer decomposition of the submartingale |Bt| into the martingale part (the integral on the right-hand side), and a continuous increasing process (local time). It can also be seen as the analogue of Itō's lemma for the (nonsmooth) absolute value function f(x)=|x|, with  f'(x) = \sgn(x) and  f''(x) = 2\delta(x) ; see local time for a formal explanation of the Itō term.

Outline of proof[edit]

The function |x| is not C2 in x at x = 0, so we cannot apply Itō's formula directly. But if we approximate it near zero (i.e. in [−εε]) by parabolas


And using Itō's formula we can then take the limit as ε → 0, leading to Tanaka's formula.


  • Øksendal, Bernt K. (2003). Stochastic Differential Equations: An Introduction with Applications (Sixth edition ed.). Berlin: Springer. ISBN 3-540-04758-1.  (Example 5.3.2)
  • Shiryaev, Albert N.; trans. N. Kruzhilin (1999). Essentials of stochastic finance: Facts, models, theory. Advanced Series on Statistical Science & Applied Probability No. 3. River Edge, NJ: World Scientific Publishing Co. Inc. ISBN 981-02-3605-0.