The Scenarios Space#
The space representing economic data
This space is parameterized with date_id and sens_id.
For each combination of date_id and sens_id values,
a dynamic subspace of this space is created,
representing a specific set of economic assumptions.
By default, the following scenarios are supported. Users should customize the contents of this space to meet their own needs.
Deterministic interest rate scenarios
Stochastic risk-neutral index return scenarios
For the interest rate scenarios,
spot_rates() in this space reads annual spot rates from an Excel file into it.
spot_rates() uses sens_is as a key to select a sheet from the file.
For the stochastic risk-neutral index return scenarios,
log_return_mth() generates stochastic returns,
from the interest rates and volatility parameters read from an Excel file.
Parameters
- date_id#
a string key representing the base date
- sens_id#
a string key representing interest rate sensitivity, which is either “BASE”, “UP” or “DOWN”.
References in the space
Example
The sample code below demonstrates how to examine the contents of
Scenarios
for specific values of date_id and sens_id, ‘202312’ and ‘BASE’.
>>> import modelx as mx
>>> m = mx.read_model("IntegratedLife")
>>> m.Scenarios['202312', 'BASE'].spot_rates()
EUR GBP JPY USD
0 0.03357 0.04735 0.00072 0.04760
1 0.02690 0.04021 0.00191 0.04056
2 0.02439 0.03668 0.00280 0.03724
3 0.02350 0.03475 0.00363 0.03571
4 0.02323 0.03355 0.00448 0.03499
.. ... ... ... ...
145 0.03241 0.03229 0.03006 0.03364
146 0.03243 0.03231 0.03010 0.03365
147 0.03244 0.03232 0.03013 0.03365
148 0.03245 0.03234 0.03016 0.03366
149 0.03247 0.03235 0.03019 0.03366
[150 rows x 4 columns]
>>> m.Scenarios['202312', 'BASE'].forward_rates()
EUR GBP JPY USD
0 0.033570 0.047350 0.000720 0.047600
1 0.020273 0.033119 0.003101 0.033567
2 0.019388 0.029656 0.004582 0.030632
3 0.020835 0.028982 0.006124 0.031134
4 0.022151 0.028764 0.007887 0.032115
.. ... ... ... ...
145 0.033861 0.033741 0.034419 0.035091
146 0.035354 0.035234 0.035957 0.035111
147 0.033911 0.033791 0.034550 0.033650
148 0.033931 0.035304 0.034610 0.035141
149 0.035454 0.033841 0.034670 0.033660
[150 rows x 4 columns]
>>> m.Scenarios['202312', 'BASE'].cont_fwd_rates()
EUR GBP JPY USD
0 0.033019 0.046263 0.000720 0.046502
1 0.020070 0.032582 0.003097 0.033016
2 0.019203 0.029225 0.004572 0.030172
3 0.020621 0.028570 0.006105 0.030659
4 0.021909 0.028358 0.007856 0.031610
.. ... ... ... ...
145 0.033300 0.033184 0.033840 0.034489
146 0.034744 0.034628 0.035325 0.034509
147 0.033349 0.033233 0.033966 0.033096
148 0.033368 0.034695 0.034024 0.034538
149 0.034840 0.033281 0.034082 0.033106
[150 rows x 4 columns]
>>> m.Scenarios['202312', 'BASE'].log_return_mth()
FUND1 FUND2 FUND3 FUND4 FUND5 FUND6
scen t
1 0 -0.030397 0.047032 -0.010060 0.000816 0.000665 -0.040567
1 -0.029103 0.025734 0.004162 -0.018741 0.084592 0.058125
2 -0.015052 0.034508 -0.005399 0.003108 0.030602 -0.070345
3 0.015784 0.051717 0.015262 0.000348 0.034553 -0.091414
4 -0.001168 0.018826 -0.015521 0.002865 0.063022 0.153368
... ... ... ... ... ...
100 1795 0.005044 0.005891 0.006421 -0.009772 0.006747 -0.018034
1796 0.005050 -0.030197 -0.027247 0.002810 -0.017504 0.011297
1797 0.070869 0.008339 0.012401 -0.002405 0.014219 -0.023541
1798 -0.001515 0.049597 0.013523 -0.015077 0.070503 0.027821
1799 0.000753 -0.019089 0.017222 0.004629 0.005042 0.000108
[180000 rows x 6 columns]
>>> m.Scenarios['202312', 'BASE'].return_mth()
FUND1 FUND2 FUND3 FUND4 FUND5 FUND6
scen t
1 0 -0.029940 0.048156 -0.010010 0.000816 0.000665 -0.039755
1 -0.028684 0.026068 0.004171 -0.018567 0.088273 0.059847
2 -0.014940 0.035111 -0.005384 0.003113 0.031075 -0.067928
3 0.015909 0.053078 0.015379 0.000348 0.035157 -0.087360
4 -0.001168 0.019004 -0.015401 0.002869 0.065050 0.165754
... ... ... ... ... ...
100 1795 0.005057 0.005909 0.006442 -0.009724 0.006770 -0.017872
1796 0.005063 -0.029746 -0.026880 0.002814 -0.017352 0.011361
1797 0.073441 0.008374 0.012478 -0.002402 0.014320 -0.023266
1798 -0.001514 0.050848 0.013615 -0.014964 0.073048 0.028211
1799 0.000753 -0.018908 0.017371 0.004640 0.005055 0.000108
[180000 rows x 6 columns]
Formulas#
Spot interest rates by duration and currency |
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Forward interest rates by duration and currency |
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Volatilities of fund indexes |
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Stochastic scenarios of fund indexes as monthly risk-neutral log returns |
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Fund index parameters |
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The number of func indexes |
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Monthly index returns |