1.8.4 Inference Procedures
In order to characterize a distribution for 
conditional on information available at time 0, we must characterize a conditional distribution for 
. We do so with an inference procedure. It is not always necessary to fully specify a distribution. We require only information sufficient to value our chosen value-at-risk metric or other PMMR.
Inference procedures take various forms. Leavens simply makes up a distribution suitable for his example. In practice, techniques of time series analysis are employed—in conjunction with financial theory—to obtain a covariance matrix for or some other reasonable characterization. We discuss inference procedures in Chapter 7.