Tokenomic Stress Testing

Implementation Details

Class Names

Model Name	Parameters Class	Data Class
TokenomicStressTesting	TokenomicStressQueryParams	TokenomicStressData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.tokenomic_stress_testing import (
    TokenomicStressTesting,
    TokenomicStressQueryParams,
    TokenomicStressData,
)

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Parameters

Name	Type	Description	Default	Optional
token_symbol	Union[str, List[str]]	Token symbol(s) to stress test (e.g., BTC, ETH, SOL).	None	True
stress_event_type	str	Event type (e.g., "Supply Shock," "Market Illiquidity," "Governance Failure").	None	True
projected_time_horizon	int	Time period (in days) to model the stress impacts.	30	True
impact_layer_focus	List[str]	Specific tokenomic layers to analyze (e.g., "Liquidity," "Holder Distribution").	None	True

---

Data

Name	Type	Description
token_symbol	str	Symbol of the token analyzed.
simulated_price	float	Predicted token price following the stress event.
liquidity_drop_percent	float	Estimated percentage of liquidity reduction during the stress period.
holder_distribution_delta	dict	Shift in token distribution across small, medium, and whale holders.
governance_impact_score	float	Impact on governance metrics, where applicable.
timestamp	datetime	Timestamp of the analysis execution.

---

Key Features

• Multi-Layer Impact Simulation: Evaluate token behavior across liquidity, governance, and market cap layers.

• Advanced Holder Behavior Modeling: Predict redistribution among holder classes after stress events.

• Scenario Customization: Design and test token-specific stress scenarios, such as early unlocking of staked tokens or major whale exits.

• Risk Amplification Metrics: Highlight cascading effects of correlated stress events across ecosystems.

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Feature Documentation: Real-Time Regulatory Risk Map

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Implementation Details

Class Names

Model Name	Parameters Class	Data Class
RegulatoryRiskMapping	RegulatoryRiskQueryParams	RegulatoryRiskData

Import Statement

pythonCopyEditfrom satoshi_terminal.models.regulatory_risk_map import (
    RegulatoryRiskMapping,
    RegulatoryRiskQueryParams,
    RegulatoryRiskData,
)

---

Parameters

Name	Type	Description	Default	Optional
region	Union[str, List[str]]	Geographic region(s) to monitor for regulatory changes (e.g., US, EU, Asia).	None	True
asset_class	Union[str, List[str]]	Type(s) of assets for regulatory analysis (e.g., "Utility Tokens," "Stablecoins").	None	True
compliance_focus	List[str]	Specific compliance areas to assess (e.g., "KYC Requirements," "AML Guidelines").	None	True
time_horizon	int	Forward-looking analysis period (in months).	6	True

---

Data

Name	Type	Description
region	str	Geographic region assessed for risk.
regulatory_score	float	Composite risk score (0-100) based on regulatory environment and compliance outlook.
recent_policy_changes	List[dict]	Details of recent policy updates impacting assets in the region.
asset_class	str	Type of asset analyzed for regulatory impact.
timestamp	datetime	Timestamp of the analysis execution.

---

Key Features

• Dynamic Region Tracking: Monitor changing regulations across multiple jurisdictions in real time.

• Asset-Specific Compliance Scoring: Provide granular compliance insights for different asset classes.

• Forward-Looking Risk Modeling: Simulate future regulatory scenarios based on policy trends and geopolitical factors.

• Regulatory Dependency Mapping: Highlight interdependencies between different regional compliance landscapes (e.g., EU-US alignment).

• Alert Triggers: Notify users of significant changes, such as a region banning or endorsing specific crypto activities.