Autoregression and decision making under uncertainty

Utkarsh Shrivastava, Gyan Prakash, Joydip Dhar, Arti Omar

Abstract


There are innumerable social and economic situations in which we are influenced in our decision making by what others are doing. Under uncertainty it’s general tendency of an individual to get inspired by decisions of others or mass opinion. However, such herd behavior many times leads to autoregressive affect i.e. output at some moment is weighted average of past few observation.  Hence can autoregressive models be used to predict the outcomes in the situations exhibiting such behavior? Studies have already been done on herd behavior in financial market. So, can models used to forecast financial markets be used to predict general decision making under uncertainty. To prove the validity of the point we conduct a small experiment of human decision making under uncertainty and try to forecast future responses using autoregressive models. A group of students were surveyed such that they can also look upon previous responses which would promote herding. A unique financial market type framework is used to quantify the responses and time series models of auto regression are used to forecast mass opinion.


Full Text: PDF DOI: 10.5539/mas.v4n8p144

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This work is licensed under a Creative Commons Attribution 3.0 License.

Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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