Risk
Time Series
Trend Analysis, Seasonal Variations, and Moving Averages for Forecasting
2 CPD credits on completion
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Certificate on completion
Downloadable resources
Self-paced learning
About This Course
Course Information
This course introduces time-series and linear processes. It also covers the three most pervasive sources of non-stationarity in financial and economic time series: time trends, seasonalities, and unit roots (more commonly known as random walks).
Certificate on Completion
This course is made up of videos, questions and additional reading materials and accounts for 2 units of CPD. A certificate will be issued once you have completed all 2 units.
Course Sections
This course is made up of the following sections:
- Stationary Time Series (video + quiz)
- Non-stationary Time Series (video + quiz)
- Additional reading materials
What You Will Learn
- Define a time series and identify its four components: trend, seasonal variations, cyclic variations, and random variations
- Explain how to plot time series data on a graph and draw a trend line to show the general direction of the data
- Calculate moving averages to estimate the trend from quarterly or monthly data
- Distinguish between seasonal and cyclic variations in business data
- Apply linear regression analysis to establish the equation of the line of best fit for forecasting
Who This Course Is For
- Accountants and finance professionals who use forecasting in budgeting or planning
- Analysts who need a practical introduction to time series methods for revenue or cost prediction
- Professionals studying for management accounting qualifications who want CPD credit for this topic
Prerequisites
- Basic arithmetic and an understanding of averages
- Familiarity with scatter diagrams and the concept of a line of best fit is helpful but not required
Frequently Asked Questions
Course Details
CPD Credits2
CertificateYes
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CPD certificate on completion
Downloadable resources
Self-paced learning
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