Linear correlation is only an adequate means of describing the dependence between two random variables when they are jointly elliptically distributed. When the joint distribution of two or more variables is not elliptical the linear correlation coefficient becomes just one of many possible ways...

The theory of conditional copulas provides a means of constructing flexible multivariate density models, allowing for time varying conditional densities of each individual variable, and for time-varying conditional dependence between the variables. Further, the use of copulas in constructing...

Dominant properties of various kinds can be defined for distributions including trends, strong seasonality, business cycles, and a persistent component. We say that in the joint distribution of X and Y, conditional on W has a common factor if W is a dominant component, but it does not appear in...

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks with varying average trade frequencies. We specify an error-correction model for the log difference of the bid and the ask price, with the spread acting as the error-correction term, and include as regressors the...