Quality Quandaries- Time Series Model Selection and Parsimony

Choosing an adequate model for a certain set of data is considered to be one of the more difficult tasks in time series analysis as experienced analysts are also having a hard time selecting such appropriate model. Thus, one popular approach have been discussed with the use of certain numerical criteria which is believed to be a useful input for the decision making process. However, using this technique solely is also not advisable on choosing a model but the use of judgement and the use of information criteria are more preferred. Specifically, the use of parsimonious mixed autoregressive model (ARMA) is more favorable to be used as it considers the context of the model as well as illustrating what is trying to be modeled and what model is to be used.