  In this paper, we study the stochastic linear complementarity problems on
extended second order cones (stochastic ESOCLCP). We first convert the problem
to a stochastic mixed complementarity problem on the nonegative orthant
(SMixCP). Enlightened by the idea of Chen and Lin(2011), we introduce the
Conditional Value-at-risk (CVaR) method to measure the loss of complementarity
in the stochastic case. A CVaR - based minimisation problem is introduced to
achieve a solution which is "good enough" for the complementarity requirement
of the original SMixCP. Smoothing function and sample average approximation
methods are introduced and the the problem is converted to a form which can be
solved by Levenberg-Marquardt smoothing SAA algorithm. At the end of the paper
a numerical example illustrates our results.
