Hi all, Big question.
1)What is a fast, reliable and market consistent methodology for calculating IV->Smile->Surface for American style, single stocks names, that have dividends, from snap-shot quote data, (1-20 min) about 4000 symbols.
Notes: Whaley, HHL, Bjerk, Binomial, Jump etc.. give approximations that are great given the inputs; in practice the market disagrees with inputs. Dividend estimates, borrows are unobtainable, and even short rates are inconsistently used. Other models seem very "sensitive", and complicated SVI/SSVI S3, CEV... and I remain unsure of what direction to go to handle a huge data set. Butterfly/Cal arb removal, well maybe in next the questions/threads...
Additional couple of questions:
1A) The market disagrees with dividend estimates, is there an implied method used in practice
1B) The market will also disagrees with short rate and borrows (just no obtainable), same question about implied method that is used in practice.
I hope that this thread can become a reference point for myself and others who are working on this issue with Vanillas. Thank you.