meenmo / isda_simm Goto Github PK

Hello,
Now, i have the following error:

C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:84: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_main = pd.concat([df_main, df_local_sensiType])
C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:90: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_risk_class = pd.concat([df_risk_class, df_local_riskType])
C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:84: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_main = pd.concat([df_main, df_local_sensiType])
C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:90: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_risk_class = pd.concat([df_risk_class, df_local_riskType])
C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:84: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_main = pd.concat([df_main, df_local_sensiType])
C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:84: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_main = pd.concat([df_main, df_local_sensiType])
C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py:90: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df_risk_class = pd.concat([df_risk_class, df_local_riskType])
Traceback (most recent call last):
File "C:\Users\dizri\Desktop\ISDA_SIMM-main\src\main.py", line 14, in
main('USD')
File "C:\Users\dizri\Desktop\ISDA_SIMM-main\src\main.py", line 9, in main
results = calc.simm()

I face the following errors:

C:\Users\dizri\Desktop\ISDA_SIMM-main\src>python main.py
Traceback (most recent call last):
File "C:\Users\dizri\Desktop\ISDA_SIMM-main\src\main.py", line 2, in
import agg_margins
File "C:\Users\dizri\Desktop\ISDA_SIMM-main\src\agg_margins.py", line 7, in
from margin_risk_class import MarginByRiskClass
File "C:\Users\dizri\Desktop\ISDA_SIMM-main\src\margin_risk_class.py", line 3, in
from scipy.stats import norm
ModuleNotFoundError: No module named 'scipy'

Could you please help me?

Hello,

Thank you for making your SIMM python codes available on GitHub. Are you planning to update for version 2.5 that was released recently? Also, have you tried running the ISDA SIMM Unit tests on your model ?
Thanks again.

Hi ,

Thank you so much , I tried to validate the ISDA Unit Test (Its free) and I have find some test that doesn't pass the test using your code.

Exemple when crif file is :

portfolio_id,trade_id,collect_regulations,product_class,risk_type,qualifier,bucket,label1,label2,amount,amount_currency,amountusd
C330,C330.S_IRV_16,All,RatesFX,Risk_InflationVol,USD,,30y,,80000000.0,USD,80000000.0
C330,C330.S_IRV_21,All,RatesFX,Risk_InflationVol,USD,,2w,,-80000000.0,USD,-80000000.0

Official unit test expect the result to be 0 and your code return a Curvature of 2,442,463.46

An other failed test :

portfolio_id,trade_id,collect_regulations,product_class,risk_type,qualifier,bucket,label1,label2,amount,amount_currency,amountusd
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0
C349,C349.S_FXV_7,All,RatesFX,Risk_FXVol,RUBTRY,,5y,,-12000000.0,USD,-12000000.0

Official unit test expect the result to be 1,898,530,683.542 and your return a Vega 1,706,855,277.77

If you have an idea to correct it and validate all unit test it will be really good. Thank you for all.