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Re: [Quantlib-users] The reason of differences between `FDDividendAmericanEngine` of QuantLib 1.12 and `FdBlackScholesVanillaEngine` of QuantLib 1.18
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From: Luigi B. <lui...@gm...> - 2020-06-18 08:52:48
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Yes, they do change. See the script I'm attaching for a simple example. Luigi On Thu, Jun 18, 2020 at 10:32 AM Luigi Ballabio <lui...@gm...> wrote: > Hmm. No, I would expect the result to change at least slightly. Let me > check that. Can you share the code you're using? > > Luigi > > > On Tue, Jun 16, 2020 at 11:02 PM Shenze Wang < > she...@da...> wrote: > >> Hi Luigi, >> >> Thanks a lot for the reply. >> >> I did not set the parameter `CashDividendModle` of the constructor >> `FdBlackScolesVanillaEngine` explicitly in my previous calculations. >> >> However, it seems that the parameter `CashDividendModle` does not affect >> the results at all. >> >> I calculated the prices of a bunch of American options with dividend >> yields with the engine `FdBlackScolesVanillaEngine` from QuantLib 1.18. >> The results from 'CashDividendModel cashDividendModel = Spot’ and the >> results from 'CashDividendModel cashDividendModel = Escrowed’ are >> *identical*, literally. I am using the Python wrap. >> >> Is this normal? >> >> >> Best, >> Shenze >> >> On Jun 16, 2020, 4:51 AM -0400, Luigi Ballabio <lui...@gm...>, >> wrote: >> >> Hello, >> thanks for the analysis. >> >> There are people here which are more capable of answering than I am, but >> just to make sure that we're comparing equals to >> equals: FdBlackScholesVanillaEngine has two possible ways to handle >> dividends, and we should document this better. One is the scale/shift >> model, and the other is the escrowed dividend model; you can choose the >> model by mans of an optional last parameter for the constructor (see < >> https://github.com/lballabio/QuantLib-SWIG/blob/master/SWIG/options.i#L1202 >> >). >> >> Now, FDDividendAmericanEngine uses the escrowed dividend model, which I'm >> told is the one described in most texts. >> Instead, FdBlackScholesVanillaEngine uses by default the scale/shift >> model. If you didn't set the model explicitly, this might be the reason >> for the differences. Passing Escrowed as the model would cause the results >> to be closer. >> >> If you did that already, though, we'll have to look closer into the code. >> >> Hope this helps, >> Luigi >> >> >> >> On Mon, Jun 15, 2020 at 10:01 PM Shenze Wang < >> she...@da...> wrote: >> >>> Hi, >>> >>> We are currently using `FD*D*ividend*A*mericanEngine` (denoted by *DA* in >>> following) of QuantLib 1.12. Since this engine is removed in QuantLib 1.16, >>> we’d like to switch to `*Fd*BlackScholesVanillaEngine` (denoted by *FD *in >>> following) of QuantLib 1.18. Before we do the switch, we’d like to know the >>> difference between these two engines (DA engine in QuantLib 1.12 and FD >>> engine in QuantLib 1.18) and what are the impacts on the pricing results. >>> We are using the Python version of QuantLib. >>> >>> I priced ~7000 options with different ivols, strikes, interest rates, >>> dividend yields with 3 engines: (a) *DA12* - `FDDividendAmericanEngine` >>> in QuantLib 1.12, (b) *FD12* - `FdBlackScholesVanillaEngine` in >>> QuantLib 1.12, and (c) *FD18* - `FdBlackScholesVanillaEngine` in >>> QuantLib 1.18. >>> >>> Here are some comparisons of the results. >>> >>> *(1)* The difference between FD18 and DA12 including two parts: the >>> difference between FD12 & DA12, and the difference between FD18 & FD12. The >>> difference between FD12 & DA12 is much greater than the difference between >>> FD18 & FD12, as shown in the following form. The form shows CDF of the >>> differences. The numbers in the form are the probability that the >>> difference is in a certain range. >>> >>> >>> *(2)* *FD12 vs DA12*. The option prices generated by FD12 is greater >>> than DA12 for in-the-money options, but lower for at-the-money and >>> out-of-the-money options. Compared to the analytical solutions, FD12 is >>> more accurate for at-the-money and out-of-the-money options, while DA12 is >>> more accurate for in-the-money options. >>> >>> >>> >>> *(3)* *FD18 vs FD12. *Though it is relatively small, there is still a >>> difference between FD18 and FD12, as shown in the following figure. >>> >>> >>> >>> So, my questions are: >>> >>> 1. Do the difference between FD12 & DA12 and the difference between >>> FD18 & FD12 described above behave as expected? >>> 2. What’s the potential reasons for these differences? >>> >>> I know the answers to these questions could be very subtle, but we’d >>> like to understand the reasons for these differences, at least to some >>> extent. I also tried to dig into the C++ codes, but I am not familiar with >>> the codes and I do not know where to start. If you could provide some >>> explanations or point me the right directions, I would be super grateful. >>> >>> Thanks a lot. >>> >>> >>> Best Regards, >>> Shenze Wang >>> >>> DataDock Solutions >>> _______________________________________________ >>> QuantLib-users mailing list >>> Qua...@li... >>> https://lists.sourceforge.net/lists/listinfo/quantlib-users >>> >> |
