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Course Criteria
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1.00 - 4.00 Credits
Cooperative education courses may be taken before a students major, minor and General Education requirements are completed, but they are not counted as part of those requirements. Cross-listed: See MATH 293/393; See ACSC 293
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3.00 Credits
Prerequisite: ACSC 370 or MATH 370 This is a capstone seminar on probabilities. It challenges the student’s preparation for the Actuarial Examination P (it was exam 1) of the Society of Actuaries and the Casualty Actuaries Society. Though Calculus will be not tested in the exam P, a sound foundation in Calculus I through III is assumed, the theory of the probability will be applied to problem solving, using classification and other approaches. Note: This course is for actuarial science majors only.
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1.00 - 4.00 Credits
No course description available.
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3.00 Credits
Prerequisite: ACSC 371 or MATH 371, Minimum grade C This course covers the following topics, Evaluation data for estimation and goodness-0f-fit to models, least square estimates of parameters, Single linear regression, multiple linear regressions, Hypothesis testing, confidence intervals in linear regression models. Topics also include Testing of models, data analysis and appropriateness of models, Linear time series models, Moving average, autoregressive and/or ARIMA models, Estimation, data analysis and forecasting with time series models, Forecast errors and confidence intervals. This course has been approved by VEE Administration Committee of Society of Actuaries to fulfill the requirements of topics in Applied Statistical Methods. Note: To receive credit for the subject from the Society of Actuaries, students will need a grade of B- or better. Cross-listed: See MATH 405
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3.00 Credits
Prerequisite: ACSC 405 This course covers the materials on the professional actuarial exam C. Topic includes Construction of Empirical Models, Estimate failure time and loss distributions using Kaplan-Meier estimator, including approximations for large data sets, Nelson- Aalen estimator. Kernel density estimators, Estimate the variance of estimators and confidence intervals for failure time and loss distributions, Estimate failure time and loss distributions with the Cox proportional hazards model and other basic models with covariates. The course will also cover the topics, Unbiasedness, Consistency, Mean squared error, Estimate the parameters of “failure time and loss distributions using, Maximum likelihood, Method of moments, Percentile matching, Bayesian procedures, Estimate the parameters of failure time and loss distributions with censored and/or truncated data. Cross-listed: See MATH 406
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3.00 Credits
Prerequisite: Approved by adviser The student is expected to identify steps in the modeling process. Specifically, the candidate is expected to be able to perform the tasks such as; apply limited fluctuation (classical)credibility including criteria for both full and partial credibility, perform Bayesian analysis using both discrete and continuous models, apply B, hlmann and B, hlmann-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, simulate both discrete and continuous random variables using the inversion Method, estimate the number of simulations needed to obtain an estimate with a given error and a given degree of confidence, use simulation to determine the p-value for a hypothesis test, use the bootstrap method to estimate the mean squared error of an estimator, and apply simulation methods within the context of actuarial models. A presentation of one project is required for the course. Note: This course combine with ACSC 406 will cover the materials for Actuarial Professional exam C.
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3.00 Credits
Prerequisite: Approved by advisor The course covers the theoretical basis of certain actuarial models and the application of those models to insurance and other financial risks. The topics include interest rate models, rational valuation of derivative securities, simulation, and risk management techniques. A thorough knowledge of calculus, probability, and interest theory is assumed. Basic knowledge of risk management is also assumed.
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3.00 Credits
Prerequisite: MATH 251, Minimum grade C- This course covers the mathematical theory of compound interest with applications to investments. Topics include accumulation of interest in discrete and continuous time, nominal and effective interest, present and future values, and annuities. This course, along with Financial Mathematics I, will cover all of the topics mentioned in the most recent Basic Education Catalog of Society of Actuaries under Exam FM Learning Objectives.
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3.00 Credits
Prerequisite: ACSC 414 This course covers the mathematical theory of compound interest with applications to investments and corporate finance. Topics include accumulation of interest in discrete and continuous time, nominal and effective interest, present and future values, annuities and variable cash flows, loans, valuation of stocks, bonds and other securities, and the assessment of corporate financial performance using standard financial models.
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3.00 Credits
Prerequisite: ACSC 414 This course covers corporate financial theory, with emphasis on mathematical models, topics include the value of common stocks, risk and return, portfolio theory, capital budgeting issues, capital structure, strategic long-term financing decisions, financial statement ratio analysis and the valuation of options including the Black- Scholes formula. A project on portfolio design and analysis is required for the course. Note: Students get grade B- or better will receive credit for Corporate Finance from the Society of Actuaries.
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