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Re: CPI Time Series Interpolation

Posted by Peter Caspers-4 on Feb 09, 2017; 10:42am
URL: http://quantlib.414.s1.nabble.com/CPI-Time-Series-Interpolation-tp18062p18067.html

Hi Charles,

I don’t think so, because InflationIndex::addFixing(d,v) writes v to each day of the applicable inflation period (in your case the whole month) containing d.

Kind Regards
Peter

On 09 Feb 2017, at 13:07, Charles Allderman <[hidden email]> wrote:

Hi Peter

Thanks for clearing that up. If I created an interpolated daily series and passed that in would this workaround work?

Thanks
Charles

On Thu, Feb 9, 2017 at 1:57 PM, Peter Caspers <[hidden email]> wrote:
Hi,

it’s not rounding, QuantLib calculates 123.92 = 123.8 + (124.2-123.8) x (10-1) / 30, i.e. takes November instead of February as the basis for the interpolation. This is due to a bug described here


There is an attempt to solve that, but this is not yet merged


Looking at that I think we also need to fix the interpolation in CPICoupon, the code for this starts here


What do you think, Francois, Luigi?

Kind Regards
Peter


On 08 Feb 2017, at 13:08, Charles Allderman <[hidden email]> wrote:

Hi

I am digging into the pricing of a CPIBond. I have this index CPI index time
series:

DATE             
2016-08-31  123.0
2016-09-30  123.2
2016-10-31  123.8
2016-11-30  124.2
2016-12-31  124.7

If I interpolate for 10 February 2017 I get:
(10.0-1)/28.0*(124.2-123.8)+123.8
123.92857142857143

Deriving the values as calculated by QuantLib using the last cash flow I
get:
principal*baseCPI/notional
123.92000000000002

So it appears to be rounded down.

The inflation index is simply created by passing in a vector of
dates(month-end date plus 1 day) and values.
inflationIndex.addFixings(dte_fixings[:len(fixData)], fixData)

So is there a way to get the full interpolated value?

Thanks
Charles











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