thesis

Can you not attach the PDF file over here, so wedon't all have to register to those forums?

Could do, but respect to the author who generously allowed me to post it at my site.sorry mate.Some people were inquiring, so this is the link.

Hi there. That seems like a really nice website you got there.With more or less discussing just about the only things I'mcurrently interested in. Nice. Also very good looking, whichdoesn't harm.How is it going to catch more users to the webpage to makeit into a more active community? I know that I will myselfbe joining your website.

Daniel,I just registered for your forum -- while I am waiting to be activated, tell me if theauthor recognized the possible absorption at zero for the SABR model,as we discussed in a lengthy thread.regards,

QuoteOriginally posted by: AlanDaniel,I just registered for your forum -- while I am waiting to be activated, tell me if theauthor recognized the possible absorption at zero for the SABR model,as we discussed in a lengthy thread.regards,Alan,Do you mean the original question QuoteBy the way, I am interested in a rigorous proof that the underlying hits zero in finite time (all beta < 1).If you know or find one, I would be interested in the details. or the Fichera functions?Roelof does not discuss Fichera in the thesis but he can answer better than I can on the applicability. He based his numerics on the papers by Pat Hagan.///On the numerics, I think the schemes used by Roelof are fairly robust because he uses exponential fitting which helps the schemes adapt to various parameter ranges. So, they would be good for some of the CEV and other problems in the SABR thread.

I am working on an american style dividend paying equity option pricing model with high moment. I am using binomial approach and edgeworth series price options. I am having problems with the distributions, When I input value for skewness and Kurtosis, i get a weird distribution. Can anyone please recommend me a good approach to incorporate skew and kurtosis (high moments) in binomial option pricing modelThanks

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I've looked through the paper briefly. It looks like the possible absorption atzero of the stock price does not play a role or necessarily cause a problem in the author's numericalcalculation of option values. But, we don't really know how accurate his results are for the SABR model.It would be natural to do some good Monte Carlo's to find out, but he doesn't. If he did,he would run into this absorption phenomena pretty immediately in the simulation and have to dealwith it.

Hi All,In the newest version (should be ready on Friday) I made some more comparisons for the heston model. The numbers look good. From a numerical perspective the SABR PDE is easier to solve than the Heston PDE since there are no drift terms in the SABR PDE.If we are lucky similar errors would occur for the SABR PDE than for the Heston PDE.If someone gives sensible calibration parameters for SABR model, the method discussed should return sensible answers. Roelof

Roelof,From my viewpoint, it is interesting to see the motivation for the boundary conditions in your chapter 8 and if they can be motivated using Fichera and then the robustness and accuracy of the FDM methods.As Alan already mentioned, do you have time to compare results with MC?

Here are some benchmark output results for FDM for the original Heston model and another more difficult model (many thanks to RS and AI for the results). It would suggest that the authors have robust methods for cross derivatives, to take one aspect of this problem.here

I have made some comments on the yanenko schemes on www.datasimfinancial.comforum.Sheppardr's work on Yanenko schemes seems to gives good results.There is some drawbacks in the method and it would be good to check results for a wide range of (market like) parameters and to compareto other methods.Mars

QuoteOriginally posted by: MarsI have made some comments on the yanenko schemes on www.datasimfinancial.comforum.Sheppardr's work on Yanenko schemes seems to gives good results.There is some drawbacks in the method and it would be good to check results for a wide range of (market like) parameters and to compareto other methods.MarsThanks,I will have a look there. edit:Thanks for the feedback. . This was a benchmark example that 4-5 people worked on (using different FDM schemes). Other examples were tried, of course. Actually, the example was from Kluge's home page . My own calculation was using the MC method (NOT FDM), so we should leave it out for moment; first, I used rand() which is really BAD and the QE schems is much better. . How did you examine mixed derivatives? . (the Kluge notation is very confusing, e.g. taking exponentials and sqrt of input parameters)

Has anyone done benchmarks (MC, FDM, ...) on Heston for large T? In fact the data is that of Kluge but not with 0.5.. maturity but 10 years.r = log(1,0005) - log(1,0375)S(0) = 123.4v(0) = 0.014328theta = 0.011876kappa = 1.98937epsilon = 0.33147rho = 0.0258519T = 10.0K = 123.4What are time and price for different grid sizes?