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Activity Number: 201 - Estimation and Inference in Complex Systems
Type: Contributed
Date/Time: Monday, August 8, 2022 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract #322811
Title: A Moving (2D, 3D, 4D) Time Series Model: Predicting the Time for the Highest Gain in a Market or Business
Author(s): Asif Shams Adnan* and Mian Arif Shams Adnan
Companies: East West University and Bowling Green State University
Keywords: Adjusted R-square; BIC; Granger’s Causality Test; Spectrum; VARMAX Model
Abstract:

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 2D, 3D and 4D time series model since it adopts the Moving Variance and Moving Shape Approaches. The resultant time series model(s) provide(s) few time points that contribute the highest variation in the prices. The money makers want to predict these time points.


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