Box Jenkins Model - Explained
What is the Box-Jenkins Model?
If you still have questions or prefer to get help directly from an agent, please submit a request.
We’ll get back to you as soon as possible.
- Marketing, Advertising, Sales & PR
- Accounting, Taxation, and Reporting
- Professionalism & Career Development
Law, Transactions, & Risk Management
Government, Legal System, Administrative Law, & Constitutional Law Legal Disputes - Civil & Criminal Law Agency Law HR, Employment, Labor, & Discrimination Business Entities, Corporate Governance & Ownership Business Transactions, Antitrust, & Securities Law Real Estate, Personal, & Intellectual Property Commercial Law: Contract, Payments, Security Interests, & Bankruptcy Consumer Protection Insurance & Risk Management Immigration Law Environmental Protection Law Inheritance, Estates, and Trusts
- Business Management & Operations
- Economics, Finance, & Analytics
Table of ContentsWhat is the Box Jenkins (B-J) Model?How is the Box-Jenkins Model Used?Forecasting Stock PricesAcademic Research on Box Jenkins Model
What is the Box Jenkins (B-J) Model?
The Box-Jenkins Model is a mathematical model used for forecasting of data following specified time series. This model reflects predictable cycles, trends and patterns of time series data. The Box-Jenkins Model analyses and accurately forecasts diverse time series data for a specified time, usually short-termed. The outcomes or results of the analysis of the Box-Jenkins model are dependent on the divergences between data points or the time series data. ARIMA (Autoregressive integrated moving average) models are forms of Box-Jenkins model. Both models can be used interchangeably, the Box-Jenkins model uses seasonal differences to pick out trends and predictable patterns in generating forecasts.
How is the Box-Jenkins Model Used?
The Box-Jenkins Model was first discussed in 1970, in a publication titled; "Time Series Analysis: Forecasting and Control." It was named after two mathematicians who created this model, they are George Box and Gwilym Jenkins. This model is used for forecasting of time series data, that is date from specified time. The data forecast can be business data, stock prices and even future security data. It is best used for short-term forecasting of time series data of 18 months and below. The Box-Jenkins model uses using autoregression model and carries out forecasting using programmed software. The Box-Jenkins Model is most suitable for data and are stable and less vulnerable. Due to complications in the estimation of the parameters of the Box-Jenkins Model, forecast is done using programmed software. The software is automatic and can be used in the analysis of different types of time series data and presenting their outcomes. Three principles, p, d and q which mean autoregression, differencing and moving average respectively are the principles of forecast that the Box-Jenkins Model uses. The autoregression (p) principle tests for immobility or stationarity in time series data while the differencing (D) principle tests for the differences between the data. The moving average (q) of the data is also tested before the outcome of the analysis can be determined.
Forecasting Stock Prices
Using the R software, the Box-Jenkins model is an effective mathematical model that forecasts stock prices. It can also analyze other business related data and forecast future security prices. The results or outcomes of the analysis conducted with the Box-Jenkins can generate forecasted prices for stocks in future time over a specified period of time.