Diagnosing a One-Year EUR Swap Rate Mismatch in Rateslib

# Rateslib - Pricing 1y EUR vs 6M (EUSA01)


# Rateslib - Pricing 1y EUR vs 6M (EUSA01)












I am using the rateslib python library to try to price some European swaps. It seems to be working for most tenors aside from the 1y for some reason.

The code I am using is below:

```
from rateslib import *
from tia.bbg import LocalTerminal
import pandas as pd

today = dt.today()
start = add_tenor(today,"2b","F",get_calendar("tgt"))
maturity = add_tenor(start,"1Y","F",get_calendar("tgt"))

eurcurve = '45'

eurcurve_id = 'YCSW' + eurcurve.zfill(4) + ' Index'
eurresp = LocalTerminal.get_reference_data(eurcurve_id,'CURVE_TENOR_RATES')
eurdf = eurresp.as_frame()
eurtenors = eurdf['CURVE_TENOR_RATES'].iloc[0]['Tenor'].to_list()
eurrates = eurdf['CURVE_TENOR_RATES'].iloc[0]['Mid Yield'].to_list()

eurdata = pd.DataFrame({"Term": eurtenors, 
                        "Rate":eurrates})

eurdata["Termination"] = [add_tenor(start,_,"F","tgt") for _ in eurdata["Term"]]

eureur = Curve(
    id = "eureur",
    convention=defaults.spec["eur_irs"]["convention"],
    calendar=defaults.spec["eur_irs"]["calendar"],
    modifier=defaults.spec["eur_irs"]["modifier"],
    interpolation="log_linear",
    nodes={
        **{today:1.0},
        **{_:1.0 for _ in eurdata["Termination"]},
    }
)
        

eur_kws = dict(
    spec="eur_irs",
    effective = start,
    curves ="eureur"
)

eursolver = Solver(
    curves=[eureur],
    instruments=[IRS(termination=_,**eur_kws)for _ in eurdata["Termination"]],
    s = eurdata["Rate"],
    instrument_labels=eurdata["Term"],
    id = "eur_rates"
)

eurdata["DF"] = [float(eureur[_]) for _ in eurdata["Termination"]]

eurirs = IRS(
    notional = -10e6,
    termination = maturity,
    **eur_kws
)

eurswaprate = eurirs.rate(solver=eursolver)

print(eurswaprate)
print(eurdata)
```

so the output from this code, looking at the rates and the discount factors vs bbg, look fine to me

Here are the BBG values

and here are the ones in 'eurdata' from my code

so these have a slightly bigger margin of error than i see in the sofr curve example in the rateslib docs but i think this is because the rates that i pull from bbg dont match exactly what the 'curves' tab in SWPM has.

Anyway, when i then print the rate out on this 1y swap i get some pretty different values.

BBG = 3.68

Me = 3.451

I thought this was just something i was doing wrong (and it likely still is). However what i found that was weird is that it seems to match much much closer (within a bp) when looking at essentially any other tenor. for example the 2y and 5y below

2y BBG = 3.4185

2y Me = 3.418

5y BBG = 3.03145

5y Me = 3.032

So my question is:

Is there something fundamentally incorrect with how I am either using the rateslib library or how i am approaching this problem? I have done my best to try and piece together from the docs but struggling to get there