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All Times EDT

Wednesday, June 3
Computational Statistics
Computational Statistics Posters
Wed, Jun 3, 1:00 PM - 4:00 PM
TBD
 

A Moving Shape (3 D) Time Series Model (308343)

*Mian Arif Shams Adnan, Bowling Green State University 

Keywords: Adjusted R-square, BIC, Correlation, Granger’s causality test, Spectrum, VARMAX Model.

A sequential approach of quickly identifying the model for the most important latent variable has been inaugurated for demonstrating the capricious behavior of the time series pattern of the original data using the optimum number of predictor(s). There are several methods in Time Series Analyses viz Moving Average Method, etc. Attempts have been made here to develop a time series model (along with the optimum number of set of characteristics or parameters) that can predict the stock prices’ pattern as well as a volatility (or volatilities). It is also called the 3D time series model since it adopts the Moving Shape Approach.