  First, we consider the problem of hedging in complete binomial models. Using
the discrete-time F\"ollmer-Schweizer decomposition, we demonstrate the
equivalence of the backward induction and sequential regression approaches.
Second, in incomplete trinomial models, we examine the extension of the
sequential regression approach for approximation of contingent claims. Then, on
a finite probability space, we investigate stability of the discrete-time
F\"ollmer-Schweizer decomposition with respect to perturbations of the stock
price dynamics and, finally, perform its asymptotic analysis under simultaneous
perturbations of the drift and volatility of the underlying discounted stock
price process, where we prove stability and obtain explicit formulas for the
leading order correction terms.
