Time Series Models


Time series analysis is a useful business forecasting technique. The concept breaks down the technicalities of time series analysis and gives a balanced overview of its strengths and drawbacks - and how to avoid pitfalls when using it.

Technique Overview

Time Series Models

Time Series Models Definition

Time series models are widely used in economics, business and engineering to predict the seasonal variability of a target variable over time, where past values are used as the input variables for the model (Matignon, 2007).

Time Series Models Description *

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Business Evidence

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Time Series Models Weaknesses *

Examples of Time Series Models *

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Business Application

Time Series Models Implementation *

Success Factors of Time Series Models *

Measures of Time Series Models *

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Professional Tools

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Further Reading

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Time Series Models References (4 of up to 20) *

  • Amihud, Y. (2002) Illiquidity and Stock Returns: Cross-section and Time-series Effects, Journal of Financial Markets, Vol. 5 pp. 31-56.
  • Bai, J. and Ng, S. (2008) Forecasting Economic Time Series using Targeted Predictors, Journal of Econometric, Vol. 146 pp. 304-17.
  • Boyer, K. and Verma, R. (2010) Operations and Supply Chain Management for the 21st Century, Cengage, Mason, OH.
  • Doganis, P., Alexandridis, A., Patrinos, P. and Sarimvei, H. (2006) Time Series Sales Forecasting for Short Shelf-life Food Products Based on Artificial Neural Networks and Evolutionary Computing, Journal of Food Engineering, Vol. 75 pp. 196-204.

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