# semantic_library/simulation_environment_definitions.yaml # Version: 1.0 # Description: Defines parameters and base states for different simulation environments # or "world models" to facilitate what-if analysis and scenario testing. # --- NOTES ON STRUCTURE --- # Each environment defines a baseline against which changes or events can be applied. # The ReasoningEngine would use these definitions to: # 1. Set up an initial state for a simulation. # 2. Apply specific scenario shocks or events. # 3. Observe how drivers (from drivers_knowledge_base.yaml) behave differently # or how their impacts are modified under this environment. # 4. Generate narratives specific to the simulation outcomes. # Key sections for each environment: # - environment_id: Unique identifier. # - description: What this environment represents. # - base_macro_factors: Default values/trends for global macroeconomic factors. # - event_definitions: A catalog of potential exogenous events specific to or # more likely in this environment, and their direct impacts. # - modification_rules_for_drivers: How parameters of drivers (defined in # drivers_knowledge_base.yaml) should be altered when this environment is active. # This allows for context-sensitive driver behavior. environments: - environment_id: BASELINE_CURRENT_MARKET_2024_Q3 description: "Represents the current assumed market conditions as of Q3 2024 (example)." tags: ["baseline", "current"] base_macro_factors: # Overrides or sets defaults for global macro factors - factor_id: MACRO_IR # Official Interest Rate currentValue: 5.25 # % trend: Stable source: "Baseline Assumption Q3 2024" - factor_id: MACRO_GDP # GDP Growth Rate currentValue: 2.0 # % annualised trend: Increasing source: "Baseline Assumption Q3 2024" - factor_id: MACRO_INFL # Inflation Rate currentValue: 2.8 # % YoY trend: Stable # Assuming it has stabilized source: "Baseline Assumption Q3 2024" - factor_id: MACRO_SC # Global Supply Chain Index currentValue: 0.5 # (Scale e.g. -2 to 2, 0.5 means slight pressure but improving) trend: Improving source: "Baseline Assumption Q3 2024" event_definitions: [] # No specific unique events for baseline, or list common ones modification_rules_for_drivers: [] # No modifications for baseline, uses defaults from drivers_knowledge_base - environment_id: SCENARIO_RECESSION_MILD_2025_H1 description: "Simulates a mild recessionary environment in the first half of 2025." tags: ["recession", "scenario", "downside"] base_macro_factors: - factor_id: MACRO_IR currentValue: 4.0 # Assumes some rate cuts in response trend: Decreasing source: "Recession Scenario V1" - factor_id: MACRO_GDP currentValue: -0.5 # Negative GDP growth trend: Decreasing source: "Recession Scenario V1" - factor_id: MACRO_INFL currentValue: 1.5 trend: Decreasing source: "Recession Scenario V1" - factor_id: MACRO_UNEMP # Unemployment Rate (assuming MACRO_UNEMP is defined in ontology) currentValue: 5.5 # % trend: Increasing source: "Recession Scenario V1" - factor_id: MACRO_CS # Consumer Sentiment Index currentValue: 55.0 # Lower sentiment trend: Decreasing source: "Recession Scenario V1" event_definitions: # Events more likely or specific to this scenario - event_id: EVT_GOV_STIMULUS_PKG_SMALL description: "Small government stimulus package announced." probability_in_scenario: 0.4 # Likelihood of this event occurring within this scenario direct_impacts: # What this event directly changes - target_variable: "MACRO_GDP.trend_modifier" # Temporary boost change_value: "+0.2pct_points_qoq_for_2q" duration: "6 months" - event_id: EVT_MAJOR_BANK_DOWNGRADE description: "A major financial institution is downgraded." probability_in_scenario: 0.2 direct_impacts: - target_variable: "market.financial_sector_sentiment" change_value: "-0.3 (on a -1 to 1 scale)" duration: "3 months" - target_driver_activation: "DRV_CREDIT_CRUNCH_RISK" # Assumed driver ID activation_probability_boost: "+0.3" modification_rules_for_drivers: # How driver parameters are changed in this environment - driver_id: DRV001 # Interest Rate Sensitivity comment: "Sensitivity to rate changes might be asymmetric in recession." # No specific parameter changes here, but could alter 'sensitivity_factor' in its impact_model - driver_id: DRV_CONSUMER_SPENDING_TRENDS # Assumed ID for a consumer spending driver impact_model_parameter_override: target_variables: ["company.financials.revenue_forecast_next_12m"] # Path to specific parameter first_order_impacts: # Identify which impact by its target or a unique ID if multiple affect same var - target: "company.financials.revenue_forecast_next_12m" # Assuming this matches a defined impact parameters: # Override parameters for the effect_function growth_factor_adjustment: -0.05 # e.g. reduce base growth expectations by 5% narrative_logic_override: explanation_patterns_llm: # Add or override LLM guidance - "Emphasize downside risks to consumer demand due to recessionary pressures." - environment_id: SCENARIO_TECH_AI_BOOM_2025 description: "Simulates a continued boom in AI and related technology sectors in 2025." tags: ["bullish", "tech_sector", "AI", "scenario"] base_macro_factors: - factor_id: MACRO_GDP # Higher GDP driven by tech currentValue: 3.5 trend: Increasing - factor_id: MACRO_VC_FUNDING # Venture Capital Funding (new factor) currentValue: "High" # Qualitative or quantitative trend: Increasing event_definitions: - event_id: EVT_AI_BREAKTHROUGH_ANNOUNCED description: "Significant AI research breakthrough announced by a major player." probability_in_scenario: 0.6 direct_impacts: - target_driver_activation: "DRV_AI_ADOPTION_ACCELERATION" # New conceptual driver activation_probability_boost: "+0.5" modification_rules_for_drivers: - driver_id: DRV006 # Innovation Pipeline Strength comment: "Higher impact of innovation in a tech boom." impact_model_parameter_override: first_order_impacts: - target: "company.valuation.pe_ratio" # Example path parameters: # e.g., increase the sensitivity of P/E to innovation metrics innovation_beta_multiplier: 1.5 - driver_id: DRV_TALENT_ACQUISITION_DIFFICULTY # New conceptual driver comment: "Increased difficulty and cost of acquiring tech talent." # This driver might become more active or its impact parameters change. # For example, its 'detection_patterns' might be met more easily, # or its 'impact_model' on 'company.financials.operating_costs' has higher parameters. activation_threshold_modifier: # Modify when this driver is detected detection_pattern_id: "PATTERN_SALARY_INFLATION_TECH" # Assumed ID of a pattern threshold_change_pct: -20 # Easier to trigger (20% lower threshold) # This structure allows for defining various baseline and alternative scenarios. # The ReasoningEngine, when running a simulation for a specific environment: # 1. Starts with the environment's base_macro_factors. # 2. Applies modification_rules_for_drivers to the general drivers_knowledge_base. # 3. Can stochastically trigger events from event_definitions. # 4. Then proceeds with identifying active drivers and calculating impacts as usual, # but now within the context of the simulated environment. - environment_id: SCENARIO_SUPPLY_SHOCK_OIL_2025 description: "Simulates a significant oil supply shock in 2025 due to geopolitical events in a major producing region." tags: ["geopolitics", "energy_crisis", "inflation_risk", "scenario"] base_macro_factors: - factor_id: MACRO_OIL_PRICE # Assuming a new MacroFactor for Oil Price (e.g., WTI $/bbl) currentValue: 120 # Spike in oil price trend: SharplyIncreasing source: "Oil Shock Scenario V1" - factor_id: MACRO_INFL # Inflation Rate currentValue: 5.5 # Spike in inflation due to energy costs trend: Increasing source: "Oil Shock Scenario V1" - factor_id: MACRO_GDP # GDP Growth Rate currentValue: 0.5 # Reduced GDP growth due to higher energy costs and inflation trend: Decreasing source: "Oil Shock Scenario V1" - factor_id: MACRO_SC # Global Supply Chain Index currentValue: 1.2 # Increased pressure on supply chains trend: Worsening source: "Oil Shock Scenario V1" event_definitions: - event_id: EVT_OIL_PRODUCER_OUTPUT_HALT description: "Major oil producer X halts 5M bpd output." probability_in_scenario: 0.85 # Core event of this scenario direct_impacts: - target_variable: "MACRO_OIL_PRICE.shock_factor" # A multiplier or additive factor change_value: "+40_USD_bbl_spike" # How the engine interprets this needs defining duration: "3-6 months" - event_id: EVT_STRATEGIC_PETROLEUM_RESERVE_RELEASE description: "Coordinated release of strategic petroleum reserves by major consuming nations." probability_in_scenario: 0.5 # Counter-measure direct_impacts: - target_variable: "MACRO_OIL_PRICE.shock_factor" change_value: "-15_USD_bbl_dampening" duration: "1-3 months" delay: "1 month" # Takes time to implement and have effect modification_rules_for_drivers: - driver_id: DRV004 # Supply Chain Disruption comment: "Exacerbated by high energy costs affecting logistics." impact_model_parameter_override: first_order_impacts: - target: "company.financials.cogs_pct_revenue" # Path to specific parameter parameters: # Override parameters for the effect_function change_amount: 0.0075 # Increase from 0.0050 due to higher energy costs - target: "company.operations.production_lead_time_days" parameters: change_amount: "Uniform(10, 45)" # Mean 27.5, up from Uniform(5,30) narrative_logic_override: explanation_patterns_llm: - "The oil supply shock significantly worsens existing supply chain disruptions (DRV004), particularly impacting logistics and input costs." - driver_id: DRV_ENERGY_COST_PASS_THROUGH # New conceptual driver for this scenario # This driver would need to be fully defined in drivers_knowledge_base.yaml. # It would model how companies can (or cannot) pass on higher energy costs. comment: "Ability of companies to pass through higher energy costs becomes critical." activation_relevance_multiplier: 2.0 # This driver becomes twice as relevant/likely to be active ...