ETM2200 · Time series analysis and stochastic processes

Overview

In this unit, you will be introduced to the theoretical foundations, statistical methodologies, and practical applications of time series analysis, stochastic processes, and machine learning for forecasting. Building on the prerequisite knowledge from Probability and Statistics I, Probability and Statistics II, Risk and Survival Modelling, and Calculus I, this unit will explore the intricacies of time series analysis and stochastic processes. The curriculum places a strong emphasis on hands-on experience, allowing you to work with real-world datasets and apply statistical tools for effective analysis. This unit will equip you with the advanced skills necessary to navigate the complexities of time-dependent data, stochastic processes, and emerging machine learning techniques in the context of actuarial analytics. By fostering a deep understanding of these methodologies and providing practical exposure, this unit prepares you to tackle real-world challenges and contribute meaningfully to the field of actuarial analytics. Upon unit completion, you will have acquired a good understanding of the theory and methodologies related to time series analysis, stochastic processes, and the use of machine learning models in forecasting, enabling you to excel in actuarial analytics, and provide sufficient expertise for use in various later units and the actuarial professional examinations.

Offerings

The Handbook publishes no offerings for this unit.

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. apply fundamental principles and concepts of Markov chains and stochastic processes for modelling
2. apply fundamental principles and concepts of time series for forecasting
3. apply fundamental principles and concepts of machine learning to solve regression and classification problems

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.