This article characterizes a family of preference relations over uncer
tain prospects that (a) are dynamically consistent in the Machina sens
e and moreover, for which the updated preferences are also members of
this family and (b) can simultaneously accommodate Ellsberg- and Allai
s-type paradoxes. Replacing the ''mixture independence'' axiom by ''mi
xture symmetry,'' proposed by Chew, Epstein, and Segal (1991) for deci
sion making under objective risk, and requiring that for some partitio
n of the state space the agent perceives ambiguity and so prefers a ra
ndomization over outcomes across that partition (proper uncertainty av
ersion), preferences can be represented by a (proper) quadratic functi
onal. This representation may be further refined to allow a separation
between the quantification of beliefs and risk preferences that is cl
osed under dynamically consistent updating.