In a Longstaff-Schwarz setting option on several underlyings can be priced using least squares monte carlo. Using suitable set of basis functions, continuation values can be approximated using backward induction, which gives suboptimal policy and a lower bound on option price.

However choice of basis functions is sometimes not trivial. Since RBFs are used quite often for approximating unknown functions I thought that RBFS should be popular choice for approximating continuation values for option pricing. However when I started searching, looking at different articles it seems like nobody uses RBFs, instead different polynomials (Chebyshev, Laguerre, Legendre) are used to approximate continuation values.

Could you please explain what is the reason for neglecting RBFs?


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