debt_leverage_profile
Net LTV ~50% on fleet; ~$1.5B total debt against ~$2.1B vessel book value; 20% rate rise adds ~$30M annual interest expense
Inferred
Agent_Inference
interest_rate_sensitivity
Mostly fixed-rate bank facilities but ~30-40% floating exposure; 20% rate increase estimated to reduce EPS by ~$0.08-0.12/share
Inferred
Agent_Inference
geopolitical_supply_exposure
Medium intensity; US-China trade tariffs on metals and components disrupt supply chains.
Medium
GICS-commodity-overlay-v1
supply_chain_dependency
Strait of Hormuz (Middle East crude loadings) and Danish Straits/Bosphorus (North Sea/Black Sea routing) are top two chokepoints
Inferred
Agent_Inference
international_expansion_readiness
Revenue denominated in USD; minimal FX devaluation risk as tanker freight rates globally priced in dollars; near-zero sovereign currency exposure
Inferred
Agent_Inference
geographic_footprint
Global VLCC operator; revenue USD-denominated regardless of trade route; no material sovereign currency devaluation exposure in top markets
Inferred
Agent_Inference
commodity_exposure_profile
Medium intensity; commodities: Steel, Aluminum, Copper, Crude Oil (fuel), Rare Earth Elements, Plastics/Resins; geopolitical: US-China trade tariffs on metals and components disrupt supply chains.
Medium
GICS-commodity-overlay-v1
vendor_lock_dependency_score
No single vendor exceeds 30% of input costs; shipyards, bunker suppliers, and ship managers are diversifiable; low lock-in risk
Inferred
Agent_Inference
business_model_type_primary
Physical asset-intensive maritime shipping; not cloud-dependent; AWS/GCP/Azure termination would cause minor back-office disruption only
Inferred
Agent_Inference
business_model_type_secondary
Asset-ownership and voyage/time-charter model; cloud infrastructure is administrative only, not operationally critical to vessel revenue
Inferred
Agent_Inference
switching_cost_profile
Minimal API coupling risk; operational technology is vessel-based; commercial systems use standard maritime software with low switching costs
Inferred
Agent_Inference
howey_test_risk_index
Primary revenue is freight income from owned vessels; clearly a traditional operating company; Howey Test not applicable, near-zero securities risk
Inferred
Agent_Inference
regulatory_burden_tier
Medium
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Limited GDPR/CCPA exposure; DHT collects minimal personal data; operations are B2B freight contracts; compliance burden is low
Inferred
Agent_Inference
antitrust_exposure_flag
VLCC market is highly fragmented globally; DHT holds <5% market share; low antitrust risk though tanker pools warrant periodic scrutiny
Inferred
Agent_Inference
regulatory_exposure_profile
Medium burden; regimes: FAA, DOT, OSHA, EPA, ITAR, FTC; Export controls and defense procurement rules create contract concentration risk.
Medium
GICS-regulatory-overlay-v1
revenue_model_type
Predominantly transactional spot voyages (~50-60%) with time-charter contracts (~40-50%) providing partial recurring revenue; no subscriptions
Inferred
Agent_Inference
monetization_vector
Per-voyage freight rate billing and daily time-charter hire; revenue directly tied to vessel utilization and spot/TC market rates
Inferred
Agent_Inference
pricing_architecture
Spot rates set by Baltic Exchange supply/demand dynamics; DHT has no unilateral pricing power; stress scenario: rate collapse to $20K/day covers opex only
Inferred
Agent_Inference
pricing_power_rating
Low individual pricing power; rate-taker in commodity freight market; offset by fleet scale and operational efficiency
Inferred
Agent_Inference
target_gross_margin_bracket
Gross margin ~55-70% at cycle highs, compressing to ~20-35% at cycle lows; highly variable with spot VLCC rates
Inferred
Agent_Inference
churn_vulnerability_index
No free-rider leakage applicable; bilateral freight contracts with major oil majors; churn risk tied to charterer credit quality, not product substitution
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is asset-linear, not headcount-linear; doubling fleet capacity requires vessel capex but minimal proportional shore-side headcount increase
Inferred
Agent_Inference
marginal_cost_of_growth
Marginal growth cost dominated by vessel acquisition (~$100M+ per VLCC); operating leverage strong once fleet acquired; sublinear headcount scaling
Inferred
Agent_Inference
franchise_compliance_risk
Not applicable; DHT operates no franchise network
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, CAC remains near-zero (brokers intermediate); unit economics hinge on vessel day rates vs. opex of ~$8,500-9,500/day per vessel
Inferred
Agent_Inference
network_effect_present
No meaningful network effects; larger fleet provides modest commercial leverage with charterers but no self-reinforcing demand network
Inferred
Agent_Inference
asset_efficiency_ratio
AI displacement risk is low; physical vessel operation requires crews and port logistics; AI can optimize routing/fuel but cannot displace core asset
Inferred
Agent_Inference
recession_resistance_tier
Moderate resilience; crude demand is relatively inelastic but tanker rates are highly cyclical; recession compresses rates but doesn't eliminate demand
Inferred
Agent_Inference
customer_segment_primary
Major international oil companies and national oil companies (e.g., Shell, Vitol, Saudi Aramco) as primary charterers
Inferred
Agent_Inference
customer_segment_secondary
Independent oil traders and refiners as secondary charterers; top 5 customers likely represent 40-60% of revenues, moderate concentration risk
Inferred
Agent_Inference
characteristic_occupations
["11-0000 Management Occupations", "13-0000 Business and Financial Operations Occupations", "15-0000 Computer and Mathematical Occupations", "17-0000 Architecture and Engineering Occupations", "23-0000 Legal Occupations", "33-0000 Protective Service Occupations", "37-0000 Building and Grounds Cleaning and Maintenance Occupations", "41-0000 Sales and Related Occupations", "43-0000 Office and Administrative Support Occupations", "47-0000 Construction and Extraction Occupations", "49-0000 Installation, Maintenance, and Repair Occupations", "51-0000 Production Occupations", "53-0000 Transportation and Material Moving Occupations"]
High
SOC-2018/GICS-overlay
agent_automatable_labor_share
0.3 (HIL — ~30% of characteristic roles agent-automatable)
Medium
SOC-2018 + agentic-exposure-v1
capital_expenditure_profile
Capital allocation split between fleet renewal (future-state: scrubber retrofits, eco-vessels) and maintaining existing VLCC fleet; no legacy stranded capex drag
Inferred
Agent_Inference
sec_cik
0001331284
High
SEC-EDGAR
ticker
DHT
High
SEC-EDGAR