Stochastic Time Series Concepts
Free SOA Exam SRM (Statistics for Risk Modeling) lesson in Time Series Models. 16 min read, ~2,423 words.
A stochastic time series decomposes into trend, seasonality, cyclical, and irregular (noise) components. Most modeling work is isolating each piece. Weak (covariance) stationarity requires constant mean, constant variance, and autocovariance that depends only on lag, not on absolute time. This is the workhorse definition on the exam. White noise has...
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What this lesson covers
- Content
- Example 1
- Example 2
- Common Mistakes
- Key Takeaways
- Exam Shortcuts
Learning objectives
- 3a
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