Return distributions in the class of pure jump limit laws are observed to reflect numerous asymmetries between the upward and downward motions of asset prices. The return distributions are modeled by self decomposable parametric laws with all parameters continuously responding to each other....

Daily asset returns are modeled using self decomposable limit laws and the structure is used to estimate the density of the uncentered data. Estimates of mean returns are a byproduct of the density estimate. Estimates of mean returns via density estimation have significantly lower standard...

Daily return distributions are modeled by pure jump limit laws that are selfdecomposable laws. The returns may be seen as composed of a sum of independent and identically distributed increments or as a selfsimilar law scaling the sum of exponentially weighted past shocks or a combination...

Models of dependence in asset returns with non-Gaussian marginals are investigated on ETF daily return data. The first is a full rank Gaussian copula. The second is a linear mixture of independent Lévy processes. The third correlates Gaussian components in a variance gamma representation. On a...

Market clichés assert that markets take escalators up and elevators down. The observation suggests differentiating models for up and down moves. Non-diffusive models allow for this and we model the move as the difference of two independent mean reverting increasing processes driven by gamma...

When the pricing kernel is U-shaped, then expected returns of claims with payout on the upside are negative for strikes beyond a threshold, determined by the slope of the U-shaped kernel in its increasing region, and have negative partial derivative with respect to strike in the increasing...