Tanaka's formula

In the stochastic calculus, Tanaka's formula states that

$|B_{t}|=\int _{0}^{t}\operatorname {sgn}(B_{s})\,dB_{s}+L_{t}$

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

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

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

$L_{t}=\lim _{\varepsilon \downarrow 0}{\frac {1}{2\varepsilon }}|\{s\in [0,t]|B_{s}\in (-\varepsilon ,+\varepsilon )\}|.$

Tanaka's formula is the explicit Doob–Meyer decomposition of the submartingale |B_t| 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 Ito's Lemma for the (nonsmooth) absolute value function $f(x)=|x|$, with $f'(x)=\operatorname {sgn}(x)$ and $f''(x)=2\delta (x)$; see local time for a formal explanation of the Ito term.

Outline of proof

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

${\frac {x^{2}}{2|\varepsilon |}}+{\frac {|\varepsilon |}{2}}.$

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

References

• Øksendal, Bernt K. (2003). Stochastic Differential Equations: An Introduction with Applications (Sixth edition ed.). Berlin: Springer. ISBN 3-540-04758-1. {{cite book}}: |edition= has extra text (help) (Example 5.3.2)
• Shiryaev, Albert N. (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. {{cite book}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)