In stochastic calculus, the Kunita–Watanabe inequality is a generalization of the Cauchy–Schwarz inequality to integrals of stochastic processes. It was first obtained by Hiroshi Kunita and Shinzo Watanabe and plays a fundamental role in their extension of Ito's stochastic integral to square-integrable martingales.[1]
Statement of the theorem
Let M, N be continuous local martingales and H, K measurable processes. Then
\( {\displaystyle \int _{0}^{t}\left|H_{s}\right|\left|K_{s}\right|\left|\mathrm {d} \langle M,N\rangle _{s}\right|\leq {\sqrt {\int _{0}^{t}H_{s}^{2}\,\mathrm {d} \langle M\rangle _{s}}}{\sqrt {\int _{0}^{t}K_{s}^{2}\,\mathrm {d} \langle N\rangle _{s}}}} \)
where the angled brackets indicates the quadratic variation and quadratic covariation operators. The integrals are understood in the Lebesgue–Stieltjes sense.
References
The Kunita–Watanabe Extension
Rogers, L. C. G.; Williams, D. (1987). Diffusions, Markov Processes and Martingales. II, Itô; Calculus. Cambridge University Press. p. 50. doi:10.1017/CBO9780511805141. ISBN 0-521-77593-0.
Undergraduate Texts in Mathematics
Graduate Studies in Mathematics
Hellenica World - Scientific Library
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