Dr. Yvonne Chueh, ASA, Ph.D., an expert in Exam STAM preparation, will provide a personalized, hands-on approach to lead students throughout this comprehensive exam preparation program, teaching exam syllabus material while preparing students to master the problem solving. Any individual who has been a previous student of Dr. Chueh knows the passion and dedication she puts forth in helping each and every student pass their exam. Learn more
The Exam STAM Preparation
Program provides the following:
- Weekly 3 hour live online class lectures each Saturday which will integrate concept building and technique practicing with problem solving. The study plan as outlined below will be adjusted according to the participants’ needs and pace. Live classes are interactive in nature and students are encouraged to ask questions of Dr. Chueh
- Reviewing and Solving of STAM problems related to lecture topics each week
- Open Forum following each live class in which students can ask questions related to any category of topics/problem solving
- Weekly quizzes to reinforce topics and problem solving reviewed each week
- Students can email Dr. Chueh each week with questions related to any category of STAM topics/problem solving
- Students can schedule times to meet privately with Dr. Chueh during weekly office hours
- Recordings of live class lectures made accessible to students following its completion each Saturday
Schedule
Live Classes & Subjects
Week 1
4/18
4/18
• 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.
Week 2
4/25
4/25
• 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.
• Relations of severity, frequency and aggregate models: Include deductibles and policy limits to modify probability distributions of loss variables to claim variables under inflation.
Week 3
5/2
5/2
• Risk Measures: Define and calculate VaR, and TVaR. Solve related problems in risk measures.
Week 4
5/9
5/9
• Parametric Models: Estimate the parameters of failure time and loss distributions using:
a) Maximum likelihood
b) Method of moments
c) Percentile matching
d) 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.
a) Maximum likelihood
b) Method of moments
c) Percentile matching
d) 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.
Week 5
5/16
5/16
• Credibility Theory: Apply limited fluctuation (classical) credibility including criteria for both full and partial credibility.
• Perform Bayesian analysis using both discrete and continuous models. Perform Bayesian analysis using both discrete and continuous models.
• Perform Bayesian analysis using both discrete and continuous models. Perform Bayesian analysis using both discrete and continuous models.
Week 6
5/23
5/23
• 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.
Week 7
5/30
5/30
• Casualty Insurance Topics
• Medical and Dental Coverage, Property and Casualty Coverage
• Medical and Dental Coverage, Property and Casualty Coverage
Week 8
6/6
6/6
• Pricing: Pure Premium and Loss Ratio.
Week 9
6/13
6/13
• Reserving: Estimating unpaid losses from a run-off triangle, using Chain ladder, Average cost per claim, Bornhuetter Ferguson.
• Average cost per claim, Bornhuetter Ferguson.
• Average cost per claim, Bornhuetter Ferguson.
Week 10
6/20
6/20
• Open Forum: Q&A
June 23-29
Exam STAM
There will be 15 semi-weekly intensive quizzes:
- Severity, Frequency, and Aggregate Loss:
Basics
Deductibles
Policy Limits
Loss Elimination Ratio - Severity, Frequency, and Aggregate Loss:
Pareto
Poisson
Gamma
Severity Coverage Modifications and Bonuses - Severity, Frequency, and Aggregate Loss:
Discrete Distributions
Frequency: Exposure & Coverage Modifications
Mixtures and Splices - Severity, Frequency, and Aggregate Loss:
Aggregate Loss Models - Risk Measures:
Risk Measures VaR and CTE, and Tail Weight - Parametric Models:
Method of Moments
Percentile Matching
Maximum Likelihood Estimators - Parametric Models:
Hypothesis Tests: Chi-square
Hypothesis Tests: Graphic Comparison
Hypothesis Tests: Kolmogorov-Smirnov
Variance of Maximum Likelihood Estimators
Fitting Discrete Distributions
Likelihood Ratio Algorithm, Schwarz Bayesian Criterion - Credibility:
Exact Credibility
Limited Fluctuation Credibility - Credibility:
Bayesian Credibility: Conjugate Priors
Bayesian Methods: Continuous Prior
Bayesian Methods: Discrete Prior - Credibility:
Buhlmann as Least Squares Estimate of Bayes
Buhlmann Credibility: Continuous Prior
Buhlmann Credibility: Discrete Prior - Credibility:
Buhlmann-Straub Credibility
Empirical Bayes Non-Parametric Methods
Empirical Bayes Semi-Parametric Methods - Pricing:
Rate Making - Reserving:
Loss Reserving - All topics in appropriate percentage
- All topics in appropriate percentage
