A new topology (called S) is defined on the space ID of functions x : [0, 1] → IR 1 which are right-continuous and admit limits from the left at each t > 0. Although S cannot be metricized, it is quite natural and shares many useful properties with the traditional Skorohod's topologies J 1 and M 1 . In particular, on the space P(ID) of laws of stochastic processes with trajectories in ID the topology S induces a sequential topology for which both the direct and the converse Prohorov's theorems are valid, the a.s. Skorohod representation for subsequences exists and finite dimensional convergence outside a countable set holds.

It is shown that in a large class of topological spaces every uniformly tight sequence of random elements contains a subsequence which admits the usual almost sure (a.s.) Skorokhod representation on the Lebesgue interval.

The aim of this paper is to provide conditions which ensure that the affinely transformed partial sums of a strictly stationary process converge in distribution to an infinite variance stable distribution. Conditions for this convergence to hold are known in the literature. However, most of these results are qualitative in the sense that the parameters of the limit distribution are expressed in terms of some limiting point process. In this paper we will be able to determine the parameters of the limiting stable distribution in terms of some tail characteristics of the underlying stationary sequence. We will apply our results to some standard time series models, including the GARCH(1, 1) process and its squares, the stochastic volatility models and solutions to stochastic recurrence equations.

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A class of stochastic processes, called "weak Dirichlet processes", is introduced and its properties are investigated in detail. This class is much larger than the class of Dirichlet processes. It is closed under C 1 -transformations and under absolutely continuous change of measure. If a weak Dirichlet process has finite energy, as defined by Graversen and Rao, its Doob-Meyer type decomposition is unique. The developed methods have been applied to a study of generalized martingale convolutions. Mathematics Subject Classification: 60G48, 60H05