Risk Modeling

A common empirical approach to assessing risk in a system such as Exocore is to apply the Monte Carlo method, which would involve creating a model that simulates a wide range of possible outcomes based on probability distributions of various input variables, such as: operational uptime, slashing history, liquidity levels, restaking yield, frequency and severity of smart contract exploits, transaction fees, cross-chain communication failures, audit trails, etc. By running a Monte Carlo simulation, insights can be gained into the probabilities of different systemic risks occurring and their potential impacts. Although a Monte Carlo experiment is out-of-scope for this whitepaper, it should be included in future work.

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