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In Finance, what are Time Series Models?

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  • Written By: Jason C. Chavis
  • Edited By: Bronwyn Harris
  • Last Modified Date: 21 March 2018
  • Copyright Protected:
    2003-2018
    Conjecture Corporation
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Within the field of finance, specifically statistics and financial mathematics, time series models are a system in which researchers can determine the likely outcome of a particular data stream. Essentially, time series models allow an analyst to forecast how well a financial security will perform over a specific interval of time. Using past events as a point of reference, time series models measure the historical data and establish a prediction of where that security stands in the future based on its previous performance. One of the most common methods of technical forecasting includes the analysis of moving averages, as used by people who study econometrics, the analysis of economic data. For example, modeling variations can be created using the performance average of a particular stock at closing bell over the course of six months, providing an acceptable prediction of its future value.

The major advantage to time series models over other forms of data forecasting is the fact that the patterns used by researchers are based on linear data rather than objective information. In addition, the closer the timeline patterns are implemented into the model, the more accurate the forecast becomes. Since financial securities change by small intervals over the course of time, the more detail added to the model, the closer approximation an analyst can make.

Economists utilizing the principles of time series models in finance use a variety of forms to successfully analyze the information. Each of these forms falls into two standards of criteria, either involving frequency or time. Time series models that analyze frequency are used to predict the amount of change by each security over time. On the other hand, the analysis of time identifies how fast a security changes over a given period. Both methods can be used, but researchers need to be aware of random events that impact the procedure, known as the stochastic process.

The person who is credited with creating the concept of time series models is Norwegian economist Ragnar Frisch, winner of the Nobel Prize in Economics in 1969 for his work in the field of finance. He developed the early research methods of econometrics with a paper in 1927. This helped create the overall theories and principles behind using historical data and technical forecasting to better analyze the future results of securities in the form of time series models.

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