[Quantlib-users] Question regarding fitting Euribor curve using different basis quotes

[Sumit S. <su...@mo...>]

Hi,

   I am trying to fit a EUR curve based on the following instruments:-

1. EONIA quotes
2. 1m vs 6m basis quotes
3. 3m (outright) quotes
4. 6m (outright) quotes
5. 6m vs 12m quotes

(1) , (3) & (4) are simply outright quotes and I fit that (using a python
optimiser) by modelling them as :-

   - EONIA is modelled as a Quantlib OvernightIndexedSwap object
   - 3m & 6m Swaps are modelled as VanillaSwap object

I am having trouble fitting the basis quotes.

*1m vs 6m basis quotes*
The quotes are as
follows:-[('1Y',12.3),('2Y',12.6),('3Y',13),('4Y',13.1),('5Y',13.1),('10Y',11.6),('20Y',6.5),('30Y',4.4)]

*6m vs 12m basis quotes  *
The quotes are as follows:-
[('1Y',7),('2Y',7.2),('3Y',7.4),('4Y',7.6),('5Y',7.7),('10Y',7.5),('20Y',6.3),('30Y',5.4)]

The *attached code* is what I use to model these basis swaps (basically I
model them as 2 VanillaSwaps  - long the long term Euribor and short the
short term Euribor)

My question is regarding which leg to use a Swap1 vs Swap2.

My understanding is , the spread is added to the libor leg of the short
tenor.

So for example, for modelling 1m vs 6m,

   - I create *VanillSwap1 object (for the 1m Euribor leg) *and *add the
   spread to the floating leg.* I then create VanillaSwap2 for the long
   tenor (i.e. 6m Euribor)


Similarly, for modelling 6m vs 12m basis,:-

   - I create *VanillSwap1 object (for the 6m Euribor leg) *and *add the
   spread to the floating leg.* I then create VanillaSwap2 for the long
   tenor (i.e. 12m Euribor)

However, I am getting negative fitted zero rate (after the optimisation
process) for the 6m vs 12m.
For the 1m vs 6m basis, I correctly fit the zero rate spreads to the market

Am I doing something wrong here?

Regards
Sumit


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