  We propose a new non-linear single-factor asset pricing model
$r_{it}=h(f_{t}\lambda_{i})+\epsilon_{it}$. Despite its parsimony, this model
represents exactly any non-linear model with an arbitrary number of factors and
loadings -- a consequence of the Kolmogorov-Arnold representation theorem. It
features only one pricing component $h(f_{t}\lambda_{I})$, comprising a
nonparametric link function of the time-dependent factor and factor loading
that we jointly estimate with sieve-based estimators. Using 171 assets across
major classes, our model delivers superior cross-sectional performance with a
low-dimensional approximation of the link function. Most known finance and
macro factors become insignificant controlling for our single-factor.
