Pages that link to "Item:Q2157210"
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The following pages link to A comprehensive model for cyber risk based on marked point processes and its application to insurance (Q2157210):
Displaying 18 items.
- Cyber claim analysis using generalized Pareto regression trees with applications to insurance (Q2034155) (← links)
- Cyber risk ordering with rank-based statistical models (Q2058552) (← links)
- Discussion on: `A comprehensive model for cyber risk based on marked point processes and its applications to insurance'' (Q2157212) (← links)
- Frequency and severity estimation of cyber attacks using spatial clustering analysis (Q2172027) (← links)
- Cyber risk frequency, severity and insurance viability (Q2172032) (← links)
- Data breaches: goodness of fit, pricing, and risk measurement (Q2364015) (← links)
- Cyber-contagion model with network structure applied to insurance (Q2682978) (← links)
- Aegis A Novel Cyber-Insurance Model (Q3098100) (← links)
- Propagation of cyber incidents in an insurance portfolio: counting processes combined with compartmental epidemiological models (Q5014492) (← links)
- Exact Insurance Premiums for Cyber Risk of Small and Medium-Sized Enterprises (Q6043850) (← links)
- Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data (Q6096596) (← links)
- Convergence rate for geometric statistics of point processes having fast decay of dependence (Q6165985) (← links)
- Modeling and pricing cyber insurance. Idiosyncratic, systematic, and systemic risks (Q6173879) (← links)
- Optimal dividend strategies for a catastrophe insurer (Q6581631) (← links)
- A bonus-malus framework for cyber risk insurance and optimal cybersecurity provisioning (Q6593148) (← links)
- Is accumulation risk in cyber methodically underestimated? (Q6649318) (← links)
- Optimal reinsurance with a systemic surplus shock (Q6665054) (← links)
- A copula model for marked point process with a terminal event: an application in dynamic prediction of insurance claims (Q6665456) (← links)