Configuration
You can manually configure the ActusService and RiskService to connect to your own hosted services. This is especially important in production environments, since the public services are intended only for demonstration and testing purposes.
Actus Service Configuration
The ActusService is responsible for simulating ACTUS financial contracts. You can configure it to connect to either a remote ACTUS server or a local Docker instance.
Below is an example showing how to configure both options and simulate a fixed-rate PAM contract.
from awesome_actus_lib import PAM, ActusService
# Minimal fixed rate PAM contract
pam_contract = PAM(
calendar="NOCALENDAR",
businessDayConvention="SCF",
statusDate="2025-01-01",
contractRole="RPA",
contractID="PAM-001",
counterpartyID="CP01",
creatorID="creator01",
cycleAnchorDateOfInterestPayment="2025-01-02",
cycleOfInterestPayment="P1YL1",
nominalInterestRate=0.03,
dayCountConvention="30E360",
currency="USD",
contractDealDate="2025-01-01",
initialExchangeDate="2025-01-02",
maturityDate="2030-01-01",
notionalPrincipal=10000.0,
premiumDiscountAtIED=0
)
# Configure ActusService with a custom URL (e.g., your own ACTUS Service)
remote_url = "https://dadfir3-app.zhaw.ch/"
actus_service_remote = ActusService(serverURL=remote_url)
# It is also possible to use a local Docker service if you have it set up.
local_url = "http://localhost:8083"
actus_service_local = ActusService(serverURL=local_url)
# Generate events using the local or remote service
event_stream = actus_service_remote.generateEvents(portfolio=pam_contract)
# Print the resulting events DataFrame
print(event_stream.events_df)
Output
Running the above script will print a pandas DataFrame containing the scheduled contract events (e.g., interest payments, maturity).
type time payoff currency nominalValue nominalRate nominalAccrued contractId
0 IED 2025-01-02T00:00 -10000.000000 USD 10000.0 0.03 0.0 PAM-001
1 IP 2025-01-02T00:00 0.000000 USD 10000.0 0.03 0.0 PAM-001
2 IP 2026-01-02T00:00 300.000000 USD 10000.0 0.03 0.0 PAM-001
3 IP 2027-01-02T00:00 300.000000 USD 10000.0 0.03 0.0 PAM-001
4 IP 2028-01-02T00:00 300.000000 USD 10000.0 0.03 0.0 PAM-001
5 IP 2029-01-02T00:00 300.000000 USD 10000.0 0.03 0.0 PAM-001
6 IP 2030-01-01T00:00 299.166667 USD 10000.0 0.03 0.0 PAM-001
7 MD 2030-01-01T00:00 10000.000000 USD 0.0 0.03 0.0 PAM-001
Risk Service Configuration
Actus used to accept risk factors directly within a simulation request. However, recent developments in the ACTUS open-source community have separated the risk service from the simulation logic. This reflects the strict methodological separation between contract simulation and market scenario configuration.
With this new structure, you first populate a RiskService with market data (e.g., interest rate curves) and then submit contracts to the ActusService. The simulation engine automatically fetches the correct risk factors from the configured risk service.
This section shows how to configure both services and run a simulation based on uploaded risk factors.
Full Example including configuration of a RiskService
import pandas as pd
from awesome_actus_lib import PAM, ActusService, RiskService, ReferenceIndex
# Create a minimal variable rate PAM contract
pam_contract = PAM(
calendar="NOCALENDAR",
businessDayConvention="SCF",
statusDate="2025-01-01",
contractRole="RPA",
contractID="PAM-002",
counterpartyID="CP01",
creatorID="creator01",
cycleAnchorDateOfInterestPayment="2025-01-02",
cycleOfInterestPayment="P1YL1",
nominalInterestRate=0.02, # base rate
dayCountConvention="30E360",
currency="USD",
contractDealDate="2025-01-01",
initialExchangeDate="2025-01-02",
maturityDate="2030-01-01",
notionalPrincipal=10000.0,
premiumDiscountAtIED=0,
cycleAnchorDateOfRateReset="2025-01-02",
cycleOfRateReset="P1YL1",
marketObjectCodeOfRateReset="ust5Y",
rateSpread=0.005
)
# Create rate curve data as a DataFrame
rf_data = pd.DataFrame({
"date": ["2025-01-01", "2026-01-01", "2027-01-01", "2028-01-01", "2029-01-01", "2030-01-01"],
"value": [0.02, 0.021, 0.022, 0.023, 0.024, 0.025]
})
# Wrap it in a ReferenceIndex
reference_index = ReferenceIndex(
marketObjectCode="ust5Y",
source=rf_data,
base=1
)
# Connect to external RiskService
risk_service_url = "https://dadfir3-riskservice.zhaw.ch/"
risk_service = RiskService(serverURL=risk_service_url)
# Upload the curve to the risk service
risk_service.upload_reference_index(reference_index, riskFactorID="ust5Y")
# Create a scenario using the uploaded curve
risk_service.create_scenario(
scenarioID="scenario1",
riskFactorDescriptors=[{"riskFactorID": "ust5Y", "riskFactorType": "ReferenceIndex"}]
)
# Connect ActusService with externalRiskService enabled
actus_service = ActusService(
serverURL="https://dadfir3-app.zhaw.ch/",
externalRiskService=True
)
# Simulate contract with external risk factors
event_stream = actus_service.generateEventsWithExternalRisk(
portfolio=pam_contract,
scenarioID="scenario1",
riskService=risk_service
)
# Print event stream
print("ReferenceIndex added Successfully\n")
print(event_stream.events_df)
Output
Running the above script will print a pandas DataFrame containing the scheduled contract events (e.g., interest payments, maturity).
ReferenceIndex added Successfully
<Response [200]>
type time payoff currency nominalValue nominalRate nominalAccrued contractId
0 IED 2025-01-02T00:00 -10000.000000 USD 10000.0 0.020 0.0 PAM-002
1 IP 2025-01-02T00:00 0.000000 USD 10000.0 0.020 0.0 PAM-002
2 RR 2025-01-02T00:00 0.000000 USD 10000.0 0.025 0.0 PAM-002
3 IP 2026-01-02T00:00 250.000000 USD 10000.0 0.025 0.0 PAM-002
4 RR 2026-01-02T00:00 0.000000 USD 10000.0 0.026 0.0 PAM-002
5 IP 2027-01-02T00:00 260.000000 USD 10000.0 0.026 0.0 PAM-002
6 RR 2027-01-02T00:00 0.000000 USD 10000.0 0.027 0.0 PAM-002
7 IP 2028-01-02T00:00 270.000000 USD 10000.0 0.027 0.0 PAM-002
8 RR 2028-01-02T00:00 0.000000 USD 10000.0 0.028 0.0 PAM-002
9 IP 2029-01-02T00:00 280.000000 USD 10000.0 0.028 0.0 PAM-002
10 RR 2029-01-02T00:00 0.000000 USD 10000.0 0.029 0.0 PAM-002
11 IP 2030-01-01T00:00 289.194444 USD 10000.0 0.029 0.0 PAM-002
12 MD 2030-01-01T00:00 10000.000000 USD 0.0 0.029 0.0 PAM-002