Firstly apologies if this has been answered elsewhere.
I am using QuantLib (via Excel) to build a "standard" bond pricing sheet: prices, yields, spline AND matched-maturity ASW.
I can price the bonds, and have successfully built a forecast (Euribor) and discount (EONIA) curve. I can use qlMakeVanillaSwap() to define a spot-start swap by tenor (eg "1y","2Y" etc) and it works fine. However I am struggling to define a "broken date" swap, ie one which starts T+2 and ends on a given date (and so usually has a short stub on the first payment), to match the bond maturity. All the examples I can find have integer year tenors.
I would be grateful if someone could point me to the right method (can be in python, C++ or Excel). Or do I have to go down the route of creating explicit fixed and floating rate schedules for the swaps?
The answer seems to be: Yes, I do have to create explicit fixed and floating rate schedules, using qlSchedule(), but it turns out to be not too onerous. NB. I am pricing a vanilla EUR ABB vs 6m Euribor swap.
As for pricing, it seems the qlMakeVanillaSwap() is doing a few helpful things in one call, but only IF your swap has a whole-period tenor (eg "1y"). I found the answer for what I wanted to do in the example sheet that came with the QuantLibXL download package.
The other thing that qlMakeVanillaSwap() is doing (in addition to creating the schedules) is setting the Pricing Engine (which is used to discount the cashflows). In the longer version you have to (a) set it yourself using qlInstrumentSetPricingEngine() and (b) pass the result of that call to the Trigger parameter of qlVanillaSwapFairRate(), to establish the calculation order.
Related
I would like to construct a spot curve from supplied bond prices. I know that the curve has to be constructed from dirty prices (i.e. the ones that include accrued interest). However, from FittedBondCurve.cpp example posted on quantlib.org, it appears that FixedRateBondHelper class is initialized with clean prices.
So, my question is: does it mean that FixedRateBondHelper takes care of computing accrued interest and converting clean price to dirty price? Or is it something that a user should do? I believe it's the former but wanted to make sure.
The helper doesn't, but the fitting algorithm does. If you look at the FittedBondDiscountCurve::FittingMethod::FittingCost::value method, you'll cringe a bit at the nested inner classes, but then you'll see that the model price is calculated by adding the discounted future cash flows and subtracting the accrued amount.
A further note: in recent releases, the bond helpers have been given the possibility to work with quoted dirty prices when bootstrapping a curve (see the last parameter of their constructors, useCleanPrice, which defaults to true but can be set to false to use dirty prices. However, the FittedBondDiscountCurve class is not yet aware of this change, and thus setting useCleanPrice to false would break the algorithm. I'll try to fix this in a future release.
I'm digging up some info about filtering the noise out of my IQ data samples in C++.
I have learned that this can be done by using a simple filter which calculates the average of last few data samples and applies it to the current sample.
Do you have any further experience with this kind of filtering or do you recommend using some existing FIR filtering library?
Thanks for your comments!
Unfortunately, it is not as simple as "just get some library and it will do all the work for you"; digital filters is a quite complicated subject.
It is easy to apply digital filter to your data only if your measurements come at fixed time intervals (known as "sample rate" in digital filters). Otherwise (if time intervals vary), it is not trivial to apply digital filters (and I suspect you might need FFT to do it, but I might be wrong here).
Digital filters (both IIR and FIR) are interesting in that as soon as you know coefficients, you don't really need a library, it is easy to write it yourself (see, for example, first picture here: https://en.wikipedia.org/wiki/Finite_impulse_response : looks simple, right?); it is finding coefficients which is tricky.
As a prerequisite to find out coefficients, you need to understand quite a lot about filters: you need to know what kind of filter you need (if it is after demodulation - you'll likely need low-pass, otherwise see comment by MSalters below), you need to understand what "corner frequency" is, and you need to realize how to map those frequencies to your samples (for example, you can say that your samples are coming once per second - or at any other rate, but this choice will affect your desired "corner frequency"). As soon as you've got this understanding of "what you need in terms of digital filters" - finding coefficients is quite easy, you can do it either in MatLab, or using online calculator, look for "digital filter calculator" in Google.
We’re using JCo 3.0 to connect to RFCs and read data from SAP R/3. We use one RFC RFC_READ_TABLE often and use a second custom RFC to read employee information. My questions revolve around a third RFC RSAQ_REMOTE_QUERY_CALL. I'm calling an ad-hoc query I built in SAP using this RFC but I’m not getting the expected results. The main problem is that it appears that SAP is ignoring one of my selection criteria and using what was saved in SAP when I originally built it. The date criterion stored in my ad-hoc is 6/23/2013. If I pass in 6/28/2013 from JCo, I get the same results as if I had passed 6/23/2013 from JCo.
We have built several ad-hoc queries whose only criteria is a personnel number and call them successfully using RFC RSAQ_REMOTE_QUERY_CALL.
Background on my ad-hoc query: reporting period of today, joining together four aspects of an employee’s information: their latest action (hire, rehire, etc.), organization (e.g. company), pay (e.g. pay scale level) and communication (e.g. email). The query will run every workday.
Here are my questions:
My ad-hoc has three selection criteria. The first two are simple strings. The third is a date. The date will vary each time the query runs. We are referencing the first criteria using SP$00001, the second with SP$00002 and the third with SP$00003. The order of the criteria changes from the ad-hoc to SQ01 (what was SP$00001 in the ad-hoc is now SP$00003). Shouldn’t we reference them in the order defined in the ad-hoc (e.g. SP$00001)?
The two simple string selections are using OPTION “EQ”. The date criteria is using OPTION GT (greater than). Is “GT” correct?
We have some limited accessibility to SAP. Is there a way to see which SP$ parameters are mapped to which criteria?
If my ad-hoc was saved with five criteria but four of them never change when I call the ad-hoc from JCo, do I just need to set the value of the one or do I need to set the other four as well?
Do I have to call this ad-hoc using a variant (function.getImportParameterList().setValue(“VARIANT”, “VARIANT_NAME”))?
Does the Reporting Period have an impact on the date criteria? I have tried changing the Reporting Period to be PNPBEGDA = today and PNPENDDA = today and noticed no change.
Is there a way in SAP to get a “declaration” of your ad-hoc (name, inputs, outputs, criteria)? I have looked at JCoFunction.toXml() and JCoFunctionTemplate. These are good if you want to see something at runtime before it goes to SAP, but I’m looking for something I can use on the JCo end to help me write Java code that matches the ad-hoc.
I have looked at length on the web for answers to my questions and have not found anything that is useful. If there is anything which would help me, please let me know.
Thanks,
LM
Since I don't know much about SQnn, I won't be able to answer all of your questions...
I don't know, sorry.
It should be, at least it's the usual operator for greater than.
Yes - set an external breakpoint right inside the function module and trace its execution while performing the RFC call. Warning: At least basic ABAP knowledge required.
I don't know, sorry.
I don't know either, sorry.
That would depend on the query, I suspect...
JCo won't be able to help you out there - it doesn't know about queries, it only knows function modules. There might be other RSAQ_* function modules to get that information though.
I played with setting up a variant in SQ01 for my query. I added some settings in the variant that solved my problem and answered several of my questions in my post. The main thing I did was add a dynamically calculated date as part of my criteria. Here's how:
1. In SQ01, access menu "Go To" -> "Maintain Variants".
2. Choose your variant and in subobjects, choose "Attributes" and click "Change".
3. In the displayed list, find your date criterion.
4. Choose "D" in Selection Variable, choose a comparison option (mine was GT for greater than), and a "Name of a Variable" (really, this is the type of dynamic date calculation you need).
5. Go back to the Subobjects panel, choose "Values" and click "Change".
6. Enter any other criteria you need in the "Program selections" section.
7. Save the variant.
By doing this, I don't need to pass anything into the query from JCo. Also, SAP will automatically update the date criteria you entered in step #4 above.
So to to answer my questions from my original post:
1 and 4. It doesn't matter because I'm no longer passing anything in from JCo.
2. "GT" is Greater Than.
3 and 7. If anyone knows, I'd really like to find out.
5. Use the name you as it is in SAP (step #2 above).
6. I still don't know, but it's not holding me up.
I'm posting this in case anyone out there needs this type of information. Thanks to Esti and vwegert for helping me out.
at the moment I am working on a regional evaluation system.
I actually want to e.g. find out how regions are composed, let us say given
a lat long coordinate and a radius. Hereby I would really like to be able to separate by type and it is also necessary for the data to be up to date.
So which API based services do you recommend, if the following factors are important:
support for lat/long coordinates with search radius
differentiation by type of location
up to date information
As far as I know Google places and qype.com offer APIs which should be able to do so.
Is there a better option or which of the both do you recommend and why?
As far as I found out only Qype and Google Places offer the APIs.
Google offers 1000 requests per day for free while Qype only offers 200,
but one could apply for multiple keys in Qype which enables you to do more requests a day.
With Qype it is possible to check the full amount of commercial establishments in range (bounding box or radius), while google places has a restriction to 60 places per request.
That is the reason why I decided to use Qype.
About whether or not the information is up to date I did not make an evaluation,
but Qype shows reasonable results when applied to Munich.
I posted this on Wilmott too, wasn't sure which would get more of a response.
I'm relatively new to the world of Quantlib (and C++ . . .), so perhaps this is quite obvious. I'm trying to figure out if Quantlib can price forward premium vanilla swaptions (OIS discounting, 3mL curve for estimation). All I can see in Quantlib in the Swaption files are inputs for one term structure for discounting. Does it use this also for estimation? Or is there a way to override it, such that I can enter two curves.
Any help, examples etc would be much appreciated (and would save me a lot of time staring at the same files hoping something jumps out at me...)!
Thanks a lot
It depends. If you want to price Bermudan swaptions, you're out of luck; QuantLib can only price them on a tree and there's no way to use the two curves.
If you want to price European swaptions, you can use the two curves in the Black formula, although I agree that it's not obvious to find that out by looking at the code. As you've probably seen already, you'll have to instantiate both an instrument (the Swaption class) and a corresponding engine (the BlackSwaptionEngine class). The constructor of the BlackSwaptionEngine takes a discount curve besides the other args, so you'll pass the OIS curve here. The constructor of the Swaption, on the other hand, takes the swap underlying the option as a VanillaSwap instance. In turn, the VanillaSwap constructor takes an IborIndex instance representing the floating-rate index to be paid; and finally, the IborIndex constructor takes the curve to be used to forecast its fixings, so that's the place where you can pass the 3mL curve. To summarize:
shared_ptr<IborIndex> libor(new GBPLibor(3*Months, forecastCurve));
shared_ptr<VanillaSwap> swap(new VanillaSwap(..., libor, ...));
shared_ptr<Instrument> swaption(new Swaption(swap, ...));
shared_ptr<PricingEngine> engine(new BlackSwaptionEngine(discountCurve, ...));
swaption->setPricingEngine(engine);
double price = swaption->NPV();
Also, note that the current released version (QuantLib 1.1) has a bug that makes it use the wrong curve at some point during the calculations. You'll want to use version 1.2, which is not yet released but can be checked out from the Subversion repository at https://quantlib.svn.sourceforge.net/svnroot/quantlib/branches/R01020x-branch/QuantLib.