REGRESSION AND TIME SERIES FOR ACTUARIES

ACTSCI 654

Course Description

Foundation of multiple regression and time series analysis with focus on business. Introduction to skills needed to become critical consumers of reports that are based on regression and time series analysis.

Prerequisties

(ACTSCI 640 , GENBUS 656 , STAT 333 , or STAT 340 ), or declared in undergraduate Business Exchange program

Satisfies

FINANCE 325 , FINANCE 330 , and ECON/FINANCE 320

Credits

2 to 3

Offered

Spring

Grade Point Average

3.23

-0.52% from Historical

Completion Rate

100%

1.75% from Historical

A Rate

21.43%

-26.54% from Historical

Class Size

-15.61% from Historical

2025 Fall Grade Distribution

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

Similar Courses

ACTUARIAL STATISTICS FOR RISK MODELING

ACTSCI 640

Introduction to statistical learning theory and methods for analyzing and modeling risks in actuarial applications. Topics include linear and nonlinear models; diagnostics and assessment of predictive models; variable and model selection; and non-supervised learning techniques.

INTRODUCTION TO TIME SERIES

STAT 349

Autocorrelation; stationarity and non-stationarity; heteroscedasticity; dynamic models; auto-regressive and moving average models; identification and fitting; forecasting; seasonal adjustment; applications for financial time series, social sciences and environmental studies.

TOPICS IN APPLIED ECONOMETRICS

ECON 718

Applied time series methods.

RISK ANALYTICS

ACTSCI 657

Develop a toolbox for modeling, communicating, and managing risk and uncertainty in business applications. Emphasis on the notation of probabilistic forecasting and introduces a predictive modeling framework that integrate modern machine learning methods with distribution-based regression models. Topics include heavy-tailed regression, count data regression, survival data analysis, feature engineering using neural networks and natural language processing, among others.

FINANCIAL ECONOMETRICS

ECON 724

Introduction to econometric analysis of financial time series. Covers linear econometric time series models, multivariate time series, volatility estimation, and estimating and testing financial econometric models.