Observation of Time Series Model

Article Id: BKAP86 | Page : 58-61
Citation :- Observation of Time Series Model .Bhartiya Krishi Anusandhan Patrika.2018.(33):58-61

Achal Lama, K.N. Singh, Vishal Gurung, Ravindra Singh Sekhawat and H.S. Roy

Address :

ICAR - Indian Agricultural Statistics Research Institute, New Delhi


In this paper an attempt has been made to highlight the basic concepts of time series models. The linear time series models such as AR, MA and ARIMA models are dealt in brief. Non-linear model such as GARCH have also been introduced along with its some unique properties. Finally, the paper is concluded with emphasis on the use of these models.


Time series ARIMA GARCH.


  1. Bera, A. K., and Higgins, M. L. (1993), ARCH Models: Properties, Estimation and Testing, Journal of Economic Survey, 7, 307-366.
  2. Bollerslev, T. (1986). Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 31, 307-327.
  3. Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (2007). Time-Series Analysis:
  4. Forecasting and Control. 3rd edition. Pearson education, India.
  5. Engle, R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of U.K. inflation. Econometrica, 50, 987-1008.
  6. Fan, J. and Yao, Q. (2003). Nonlinear time series:nonparametric and parametric methods. Springer, U.S.A.
  7. Taylor, S. J. (1986). Modeling financial time series. Wiley, New York.

Global Footprints