Dr. Yvonne Chueh, ASA, Ph.D., is a Full Professor of Actuarial Science at Central Washington University with more than 20 years of experience in preparing students to pass their SOA exams. She has served as a Council Member and Chair of the SOA Education & Research Special Interest Section. Dr. Chueh’s knowledge of STAM material is unparalleled and during this five-week intensive bootcamp will use her tremendous STAM teaching experience to provide a personalized, hands-on approach in leading students to be in strong position to pass Exam STAM in June. Learn more
The Exam STAM 6-Week Bootcamp offers students the following:
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Weekly 3 hour live lectures integrating concept building with significant focus on problem solving improvement
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Open Forum immediately following each weekly lecture in which students can ask Dr. Chueh questions related to any topic/problem solving
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Weekly online assessment quizzes to monitor students progress
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Weekly Online Office Hours with Dr. Chueh
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Mini-Sessions in which students can schedule private sessions with Dr. Chueh
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Q & A Email Correspondence in which students can email Dr. Chueh questions with quick reply back
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Access to STAM Program Google Drive offering a significant amount of problem solving content
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Students can join The Exam STAM Discussion Group open only to program members to communicate with each other and Dr. Chueh
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All weekly lectures recorded and available to students
Schedule
Live Classes & Subjects
Seminar 1: 4/23
10:00 AM - 1:00 PM EST
10:00 AM - 1:00 PM EST
Severity, Frequency, and Cost Per Loss v.s. Per Payment Variables
• Severity Models: study the random variable of loss amount, with deductible or limit or both.
• Frequency Models: study the random variable of loss count, with deductible or limit or both. The class of (a,b,0) and (a,b,1) are the main model to master.
• Cost per loss and Cost per payment variables and their probability distributions, expected values, variance.
• Severity Models: study the random variable of loss amount, with deductible or limit or both.
• Frequency Models: study the random variable of loss count, with deductible or limit or both. The class of (a,b,0) and (a,b,1) are the main model to master.
• Cost per loss and Cost per payment variables and their probability distributions, expected values, variance.
Seminar 2: 4/30
10:00 AM - 1:00 PM EST
10:00 AM - 1:00 PM EST
Aggregate Claims, Compound Variables with Modified Distributions
• Aggregate Models: Express an aggregate claim model using primary and secondary distributions. Relate to their parameters or statistics for collective risk models. Recognize and define the distribution of an aggregate claim variable.
• Relations of severity, frequency and aggregate models: Include deductibles and policy limits to modify probability distributions of loss variables to claim variables under inflation.
• Aggregate Models: Express an aggregate claim model using primary and secondary distributions. Relate to their parameters or statistics for collective risk models. Recognize and define the distribution of an aggregate claim variable.
• Relations of severity, frequency and aggregate models: Include deductibles and policy limits to modify probability distributions of loss variables to claim variables under inflation.
Seminar 3: 5/7
10:00 AM - 1:00 PM EST
10:00 AM - 1:00 PM EST
Tail Distributions and Parametric Model Fitting and Testing
• Risk Measures: Define and calculate VaR, and TVaR. Solve related problems in risk measures.
• Parametric Models: Estimate the parameters of failure time and loss distributions using:a) Maximum likelihoodb) Method of momentsc) Percentile matchingd) Bayesian procedures
• Accept or reject a fitted model and/or compare models: by Graphical procedures or one of the following: Kolmogorov-Smirnov test, Chi-square goodness-of-fit test, Likelihood ratio test, Schwarz Bayesian Criterion, Akaike Information Criterion
• Risk Measures: Define and calculate VaR, and TVaR. Solve related problems in risk measures.
• Parametric Models: Estimate the parameters of failure time and loss distributions using:a) Maximum likelihoodb) Method of momentsc) Percentile matchingd) Bayesian procedures
• Accept or reject a fitted model and/or compare models: by Graphical procedures or one of the following: Kolmogorov-Smirnov test, Chi-square goodness-of-fit test, Likelihood ratio test, Schwarz Bayesian Criterion, Akaike Information Criterion
Seminar 4: 5/14
10:00 AM - 1:00 PM EST
10:00 AM - 1:00 PM EST
Credibility Theory and Applications
• Credibility Theory: Apply limited fluctuation (classical) credibility including criteria for both full and partial credibility. Perform Bayesian analysis using both discrete and continuous models.
• Credibility Theory: Apply Bühlmann and Bühlmann-Straub models and understand the relationship of these to the Bayesian model. Apply conjugate priors in Bayesian analysis and in particular the Poisson-gamma model. Apply empirical Bayesian methods in the nonparametric and semiparametric cases.
• Credibility Theory: Apply limited fluctuation (classical) credibility including criteria for both full and partial credibility. Perform Bayesian analysis using both discrete and continuous models.
• Credibility Theory: Apply Bühlmann and Bühlmann-Straub models and understand the relationship of these to the Bayesian model. Apply conjugate priors in Bayesian analysis and in particular the Poisson-gamma model. Apply empirical Bayesian methods in the nonparametric and semiparametric cases.
Seminar 5: 5/21
10:00 AM - 1:00 PM EST
10:00 AM - 1:00 PM EST
Rate Making, Reserving, and Insurance Coverages
• Casualty Insurance Topics
• Medical and Dental Coverage, Property and Casualty Coverage
• Pricing: Pure Premium and Loss Ratio
• Reserving: Estimating unpaid losses from a run-off triangle, using
• Chain ladder
• Average cost per claim
• Bornhuetter Ferguson
• Casualty Insurance Topics
• Medical and Dental Coverage, Property and Casualty Coverage
• Pricing: Pure Premium and Loss Ratio
• Reserving: Estimating unpaid losses from a run-off triangle, using
• Chain ladder
• Average cost per claim
• Bornhuetter Ferguson
Seminar 6: 5/28
10:00 AM - 1:00 PM EST
10:00 AM - 1:00 PM EST
Review and Q&A
Join The Exam STAM 6-Week Bootcamp to Greatly Advance Both Your Conceptual Understanding of STAM Topics and Problem Solving Skills to Pass Exam STAM During the June Sitting
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