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Time series analysis and stochastic processes

ETM2200

Synopsis

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.

Sourced from the Monash Handbook 2026.

Quick facts

Credit points
6
Level
2
Audience
Undergraduate
Type
Coursework
School
Faculty of Business and Economics
Faculty
Department of Econometrics and Business Statistics
Handbook year
2026

Prerequisites (1)

What it unlocks (1)