  Within the context of risk integration, we introduce in risk measurement
stochastic holding period (SHP) models. This is done in order to obtain a
`liquidity-adjusted risk measure' characterized by the absence of a fixed time
horizon. The underlying assumption is that - due to changes on market liquidity
conditions - one operates along an `operational time' to which the P&L process
of liquidating a market portfolio is referred. This framework leads to a
mixture of distributions for the portfolio returns, potentially allowing for
skewness, heavy tails and extreme scenarios. We analyze the impact of possible
distributional choices for the SHP. In a multivariate setting, we hint at the
possible introduction of dependent SHP processes, which potentially lead to non
linear dependence among the P&L processes and therefore to tail dependence
across assets in the portfolio, although this may require drastic choices on
the SHP distributions. We also find that increasing dependence as measured by
Kendall's tau through common SHP's appears to be unfeasible. We finally discuss
potential developments following future availability of market data.
