Exam ALTAM · Survival Models for Contingent Cash Flows · Free Lesson

Calculate maximum likelihood estimates of transition intensities and probabilities for multiple state and multiple decrement models, assuming piecewise constant transition intensities.

Free SOA Exam ALTAM (Advanced Long-Term Actuarial Mathematics) lesson in Survival Models for Contingent Cash Flows. 12 min read, ~1,798 words.

You watch a portfolio of disability-income policies for a year. Twenty-three active lives became disabled, nine died directly from the active state, and fourteen disabled lives died. The active cohort logged 1,840 person-years of exposure; the disabled cohort logged 312. Those five numbers, plus the assumption that intensities are constant inside an age band, are everything you need to build the MLE.

A life under observation contributes two kinds of information. While occupying state ii, it contributes a survivorship factor exp⁡(−μi∙t)\exp(-\mu^{i\bullet} t), where μi∙=∑j≠iμij\mu^{i\bullet} = \sum_{j \neq i} \mu^{ij} is the total force out of ii. At a transition i→ji \to j, it contributes the intensity μij\mu^{ij}.

L=∏i[exp⁡ ⁣(−μi∙vi)∏j≠i(μij)dij]L = \prod_{i} \left[ \exp\!\left(-\mu^{i\bullet} v^{i}\right) \prod_{j \neq i} \left(\mu^{ij}\right)^{d^{ij}} \right]

Here viv^{i} is the total central exposure in state ii (sum of time all lives spent there) and dijd^{ij} counts observed i→ji \to j transitions.

Logging converts the product into a sum, so each (i,j)(i,j) pair contributes an independent term you can maximize on its own.

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Exam shortcut

Write down a "transitions over exposure" table before any algebra. Rows are origin states, columns are destinations, cells are dij/vid^{ij}/v^{i}. The diagonal stays blank. DECISION: One band asked → use e−μi∙he^{-\mu^{i\bullet} h} and the ratio formula directly. Multiple bands asked → chain via a+bpii=apii⋅bpii{}_{a+b}p^{ii} = {}_{a}p^{ii} \cdot {}_{b}p^{ii} with each factor band-specific. For competing decrements, q(j)=(μ(j)/μ(τ))(1−e−μ(τ))q^{(j)} = (\mu^{(j)}/\mu^{(\tau)})(1 - e^{-\mu^{(\tau)}}). Memorize the split-then-scale pattern; it recurs everywhere intensities are constant.

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