  Starting from a representation of the early time evolution of a dynamical
system in terms of the polynomial expression of some observable f (t) as a
function of the time variable in some interval 0 < t < T, we investigate how to
extrapolate/forecast in some optimal stability sense the future evolution of
f(t) for time t>T. Using the functional renormalization of Yukalov and Gluzman,
we offer a general classification of the possible regimes that can be defined
based on the sole knowledge of the coefficients of a second-order polynomial
representation of the dynamics. In particular, we investigate the conditions
for the occurence of finite-time singularities from the structure of the time
series, and quantify the critical time and the functional nature of the
singularity when present. We also describe the regimes when a smooth extremum
replaces the singularity and determine its position and amplitude. This extends
previous works by (1) quantifying the stability of the functional
renormalization method more accurately, (2) introducing new global constraints
in terms of moments and (3) going beyond the ``mean-field'' approximation.
