  Laplace distribution is popular in the field of economics and finance. Still,
data sets often show a lack of symmetry and a tendency of being bounded from
either side of their support. In view of this, we introduce a new family of
skew distribution using the skewing mechanism of Azzalini (1985), namely,
skew-symmetric-Laplace-uniform distribution (SSLUD). Here uniform distribution
is used not only to introduce skewness in Laplace distribution but also to
restrict distribution support on one side of the real line. This paper provides
a comprehensive description of the essential distributional properties of
SSLUD. Estimators of the parameter are obtained using the method of moments and
the method of maximum likelihood. The finite sample and asymptotic properties
of these estimators are studied using simulation. It is observed that the
maximum likelihood estimator is better than the moment estimator through a
simulation study. Finally, an application of SSLUD to real-life data on the
daily percentage change in the price of NIFTY 50, an Indian stock market index,
is presented.
