Efficacy of Holt-Winters forecast on seasonal time series crop insurance data with structural outliers

The study analyses the components of time series data on crop insurance of the state of Tamil Nadu, India. The data was found to be seasonal and exponentially increasing. Multiplicative Holt-Winters Model was applied in order to do short range forecast. The model was run in Ms-Excel in order to understand the basics of times series forecasting. Minimum MSE value was the criteria used to find the better fitting smoothing values. The residual of the model was examined for the fit of the model. Residual mean value was close to zero. Residuals are tested for autocorrelation with Durbin-Watson test and Runs test. Histogram of residuals implies a normal distribution. Presence of outliers are detected using 3IQR method and the identified outliers are part of the structure of data and need not be removed. However, alternate models of Holt-Winters itself which are robust to work with outliers are reviewed.