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CS2: Risk Modeling and Survival Analysis
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Module 1
Actuarial Applications of Markov Processes
Building Multi-State Markov Models for Actuarial Applications
Set up multi-state Markov models for actuarial applications (e.g., healthy-sick-dead).
2
Multi-step Transitions with Chapman-Kolmogorov
Apply Chapman-Kolmogorov equations to calculate multi-step transition probabilities in actuarial multi-state models.
3
Absorption Probabilities and Expected Time to Absorption
Calculate absorption probabilities and expected time to absorption in actuarial contexts.
4
Understanding and Applying the Poisson Process in Insurance
Define the Poisson process and apply its properties to model insurance claim arrivals.
5
Compound Poisson Process: Moments and MGF
State and apply formulas for the mean, variance, and moment generating function of a compound Poisson process.
6
Compound Poisson Process Aggregates
Calculate aggregate claim probabilities and conditional expectations for compound Poisson processes.
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Continuous-Time Markov Jump Processes