6533b835fe1ef96bd129fe4f

RESEARCH PRODUCT

Interpolation and approximation in L2(γ)

Stefan GeissMika Hujo

subject

Discrete mathematicsNumerical AnalysisHermite polynomialsGeneric propertyApplied MathematicsGeneral MathematicsLinear equation over a ringGaussian measuresymbols.namesakeWiener processsymbolsBesov spaceMartingale (probability theory)Real lineAnalysisMathematics

description

Assume a standard Brownian motion W=(W"t)"t"@?"["0","1"], a Borel function f:R->R such that f(W"1)@?L"2, and the standard Gaussian measure @c on the real line. We characterize that f belongs to the Besov space B"2","q^@q(@c)@?(L"2(@c),D"1","2(@c))"@q","q, obtained via the real interpolation method, by the behavior of a"X(f(X"1);@t)@[email protected]?f(W"1)-P"X^@tf(W"1)@?"L"""2, where @t=(t"i)"i"="0^n is a deterministic time net and P"X^@t:L"2->L"2 the orthogonal projection onto a subspace of 'discrete' stochastic integrals x"[email protected]?"i"="1^nv"i"-"1(X"t"""i-X"t"""i"""-"""1) with X being the Brownian motion or the geometric Brownian motion. By using Hermite polynomial expansions the problem is reduced to a deterministic one. The approximation numbers a"X(f(X"1);@t) can be used to describe the L"2-error in discrete time simulations of the martingale generated by f(W"1) and (in stochastic finance) to describe the minimal quadratic hedging error of certain discretely adjusted portfolios.

https://doi.org/10.1016/j.jat.2006.06.001