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On the rate of convergence in the weak invariance principle for dependent random variables with applications to Markov chains

Ion Grama, Émile Le Page, Marc Peigné (2014)

Colloquium Mathematicae

We prove an invariance principle for non-stationary random processes and establish a rate of convergence under a new type of mixing condition. The dependence is exponentially decaying in the gap between the past and the future and is controlled by an assumption on the characteristic function of the finite-dimensional increments of the process. The distinctive feature of the new mixing condition is that the dependence increases exponentially in the dimension of the increments. The proposed mixing...

On the supremum of random Dirichlet polynomials

Mikhail Lifshits, Michel Weber (2007)

Studia Mathematica

We study the supremum of some random Dirichlet polynomials D N ( t ) = n = 2 N ε d n - σ - i t , where (εₙ) is a sequence of independent Rademacher random variables, the weights (dₙ) are multiplicative and 0 ≤ σ < 1/2. Particular attention is given to the polynomials n τ ε n - σ - i t , τ = 2 n N : P ( n ) p τ , P⁺(n) being the largest prime divisor of n. We obtain sharp upper and lower bounds for the supremum expectation that extend the optimal estimate of Halász-Queffélec, s u p t | n = 2 N ε n - σ - i t | ( N 1 - σ ) / ( l o g N ) . The proofs are entirely based on methods of stochastic processes, in particular the metric...

Performance of hedging strategies in interval models

Berend Roorda, Jacob Engwerda, Johannes M. Schumacher (2005)

Kybernetika

For a proper assessment of risks associated with the trading of derivatives, the performance of hedging strategies should be evaluated not only in the context of the idealized model that has served as the basis of strategy development, but also in the context of other models. In this paper we consider the class of so-called interval models as a possible testing ground. In the context of such models the fair price of a derivative contract is not uniquely determined and we characterize the interval...

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