Complex Model Considerations

Risks in the financial industry generally come from market risks, credit risks, and operational risks. These risks are also increasingly appearing in the ever-growing financial ecosystem on the chain. The bridging of risks often indicates the continuous spiral integration of the two worlds of finance. Centauri Finance took the lead in boldly trying many classic probability theories, operational research theories, and modern financial risk management models in the decentralized on-chain financial system. In this white paper, a general basic model theory is given, based on Markov The risk model of the chain helps to test the robustness of the entire system, timely control the key global data of the system, and assists in the formulation of rate policies, moving towards a professional modern financial risk management mechanism on the chain.

In addition, Centauri Finance's unique internal circulation mechanism and liquidity mechanism have a certain reference effect on the risk of extreme contract system risk, and a model similar to a reserve pool can also be established for quantitative analysis. In more complex modeling (as the scale of stablecoins on the chain and the boundary of influence expand, financial instability factors gradually increase), the covariate is not fixed, but changes in a certain distribution characteristic over time, so In the loss distribution model, the calculation of the conditional probability should actually take the probability-weighted average, and it may even be necessary to construct a non-homogeneous transition matrix and establish a more complex dual time series model.