The preparatory seminar for CAS Exam 4/ SOA Course C is five days, taught by Mr Howard Mahler (8 am to 5 pm each day). The tuition for the course is $695, payable to New England Actuarial Seminars. The seminar will be held

At the Crowne Plaza in Rosemont, Illinois, on April 8-12, 2011.

Mr Howard Mahler is a nationally acclaimed actuary as well as past Chairman of the CAS Examination Committee. He has published dozens of major research papers, and he was the recipient of the 1987 CAS Dorweiler prize. He has taught NEAS seminars since 1994 (Courses 3 and 4 and CAS Exam 5).

Mahler’s Guides for Course C /Exam 4 are unparalleled in their scope and clarity. Seminar participants receive the full set of manuals (covering the entire syllabus): 4400 pages of material. Including 3000 practice problems and about 1500 past exam questions, all with complete solutions. Sample pages are on the NEAS web page.

• "Mahler’s Guide to Frequency Distributions"
• "Mahler’s Guide to Loss Distributions"
• "Mahler’s Guide to Aggregate Distributions"
• "Mahler’s Guide to Risk Measures"
• "Mahler’s Guide to Fitting Frequency Distribution"
• "Mahler’s Guide to Fitting Loss Distribution"
• "Mahler’s Guide to Survival Analysis"
• "Mahler’s Guide to Classical Credibility"
• "Mahler’s Guide to Conjugate Priors"
• "Mahler’s Guide to Simulation"
• "Mahler’s Guide to Semiparametric Estimation"
• "Mahler’s Guide to Empirical Bayesian Credibility"
• "Mahler’s Guide to Bühlmann Credibility and Bayesian Analysis"
• Practice Exams written by Mr. Mahler

Some candidates are unable to attend an NEAS seminar. Because Mahler’s materials are  invaluable for exam preparation, they are sold separately: $385 for the Joint Exam 4/C  material, plus postage (see web site or brochure for charges by location and by type of mail, or contact the NEAS office). All seminar participants receive the full set of manuals.

 Seminar Sessions:

The seminar is fast paced, covering much material in a limited time. Students who have gone through much of the syllabus and come prepared with questions benefit most from the seminar.

Mr. Mahler provides the written material in advance, to give each student the opportunity to master each topic. During the seminar, he highlights the important parts of each subject, illustrating with numerical examples. Sample problems are discussed in detail during the seminar. . Sessions are 4 hours each, from 8:00 am to 12:00 noon and 1:00 pm to 5:00 pm

Session I-A: Frequency Distributions: Means, modes, medians, variances, and standard deviations; Binomial Distribution; Poisson Distribution; Geometric Distribution, Negative Binomial Distribution; Normal Approximation; Skewness; Probability Generating Functions; (a,b,0) class of frequency distributions; Accident Profiles; Zero-Truncated Distributions; Zero-Modified Distributions; Mixed Frequency Distributions; Gamma Function, Gamma-Poisson

Session I-B: Loss Distributions – Fundamentals: Ungrouped Data; Expected values and higher moments: means, modes, medians, variances, and standard deviations, Coefficient of Variation, Skewness, Kurtosis; Limited Losses, Losses Eliminated, Excess Losses; Layers of Loss.

Session II: Loss Distributions – Intermediate: ; Average Size of Losses in an Interval; Grouped Data; Uniform Distribution; Policy Provisions; Truncation; Censoring; Amount per Payment; Amount per Loss; Definitions; Modeling Process; Exponential Distribution; Single Parameter Pareto Distribution, Pareto Distribution; Gamma Distribution; LogNormal Distribution; Weibull Distribution; Parametric Families, parameters of loss distribution; creating additional loss distributions; Tails of Loss Distributions; Limited Expected Value; Limited Higher Moments; Mean Excess Loss; Hazard Rates; Loss Elimination Ratio.

Session III-A: Loss Distributions – Advanced: Effects of Inflation; Mixture of Models; Spliced Models

Session III-B: Aggregate Distributions: Introduction; working with Convolutions Generating Functions; Variance; Individual Risk Model; Recursive Method; Discretization; Stop Loss Premiums

Session IV-A: Classical Credibility: Credibility; Full Credibility for Frequency; Full Credibility for Severity; Process Variance of Pure Premiums and Aggregate Losses; Full Credibility for Pure Premiums; Partial Credibility

Session IV-B: Bayesian Analysis: Conditional Distributions; Bayes Theorem; Bayesian Estimation; Target Shooting Example.; Expected Value of the Process Variance, Variance of Hypothetical Means

Session V-A Risk Measures: Standard Deviation, Value at Risk; Tail Value at Risk, Monte-Carlo Simulation.

Session V-B: Fitting Frequency Distributions: Method of Moments, Maximum Likelihood; Chi-Square Statistic, degrees of freedom, p-value; Likelihood Ratio Test, Fitting to (a,b,1) distributions

Session V-C: Fitting Loss Distributions- Basic: Ogives, Histograms; Kernel Smoothing; Estimation of Percentiles; Percentile Matching; Method of Moments; Method of Maximum Likelihood

Session VI-A: Bühlmann Credibility: Bühlmann’s Credibility Parameter; Greatest Accuracy Credibility, Bühlmann-Straub Credibility Formula; Relation of Bayesian Analysis and Bühlmann Credibility; Die-Spinner Examples; Loss Functions; Least Squares Credibility; Normal Equations.

Session VI-B: Conjugate Priors - Mixing Poisson Distributions; Gamma-Poisson

Session VII: Fitting Loss Distributions-Intermediate: Chi-Square Test; Loglikelihood Ratio Test; Hypothesis Testing; Schwarz Bayesian Criterion; Kolmogorov-Smirnov Statistic; p-p plots; Anderson-Darling Statistic; Fitting to Truncated Data, Fitting a Single Parameter Pareto Distribution, Fitting to Censored Data; Fitting to Truncated and Censored Data; Properties of Estimators; Variance of Estimated Parameters

Session VIII -A: Semi Parametric Estimation.

Session VIII-B: Empirical Bayesian Techniques: No variation in Exposures; Variation in Exposures; Use of an A Priori Mean.

Session VIII-C: Conjugate Priors- Advanced: Beta-Bernoulli; Inverse Gamma - Exponential; Normal-Normal; Linear Exponential Families.

Session IX-A: Fitting Loss Distributions-Advanced: Variance of Functions of Estimated Parameters, Information Matrix, Gradient Vector, Delta Method

Session IX-B: Survival Analysis – Fundamentals: Empirical Survival Function, Kaplan-Meier Product Limit Estimator; Nelson-Aalen Estimator

Session X-A: Survival Analysis-Advanced: Log-Transformed Confidence Intervals; Maximum Likelihood; Multiple Decrements

Session X-B: Simulation: Uniform Random Numbers, Simulating Continuous Distributions, Simulating Discrete Distributions, Normal Distribution, LogNormal Distribution, Simulating Aggregate Losses and Compound Models; Deciding How Many Simulations to Run; Simulating a Gamma and Related Distributions; Simulating Mixture of Models; Simulating Splices; Bootstrapping, Bootstrapping via Simulation; Estimating p-values via Simulation.

Samples of Mahler aids: