Title :
Forecast of U.S. retirement assets using unbiased Grey-Fuzzy-Markov Chain Method
Author_Institution :
Department of Economics, Tulane University, New Orleans, USA
Abstract :
This paper presents an unbiased grey-Markov chain method to forecast the total retirement assets and the value of assets in 401(k) accounts, along with other defined contribution (DC) saving plans within years from 2015 to 2019. The prediction method integrates the unbiased grey model GM(1,1) and Markov chain method with fuzzy classification. This method takes advantage of the prediction power of the unbiased version of the Grey model GM(1,1) and improves it by introducing the fuzzy-Markov chain model to overcome the random fluctuation existed in the data. The prediction result shows a rising level on total assets earmarked for retirement, and also reveals an increasing proportion of 401(k) assets in total retirement assets.
Keywords :
"Retirement","Predictive models","Data models","Markov processes","Fluctuations","Market research"
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2015 4th International Conference on
DOI :
10.1109/ICCSNT.2015.7490811