  It is shown that the the popular least squares method of option pricing
converges even under very general assumptions. This substantially increases the
freedom of creating different implementations of the method, with varying
levels of computational complexity and flexible approach to regression. It is
also argued that in many practical applications even modest non-linear
extensions of standard regression may produce satisfactory results. This claim
is illustrated with examples.
