3 votes

L2 Assumptions of the Longstaff Schwartz method

1) Do we need to deal with infinite dimensional spaces? Yes, I think you need an infinite dimensional pay-off space. Your remark that a finite sample spans a finite dimensional space of pay-offs is ...
g g's user avatar
  • 1,973
2 votes

Foresight bias in least square monte carlo

Recently, I co-authored a paper (Arxiv | SSRN) on the issue. You can efficiently remove the look-ahead bias (a.k.a., foresight bias) using leave-out-out-cross-validation (LOOCV) method. Basically, ...
jChoi's user avatar
  • 1,143
2 votes

Foresight bias in least square monte carlo

This study seems to be on point: http://christian-fries.de/finmath/foresightbias/Fries_ForesightBias.pdf
Yian Pap's user avatar
  • 511
1 vote

Longstaff Schwartz algorithm

As Alex C says in the comments, Longstaff and Schwarz did consider multiple factors and mention it as one of the advantages (page 114 in the journal): By its nature, simulation is a promising ...
Bob Jansen's user avatar
  • 8,436

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