Date of Award

Summer 8-2021

Document Type


Degree Name

Master of Science (MS)



First Advisor

Xiyuan Liu


In this paper, we present how to use Hidden Markov Models (HMM) to predict the change in Unemployment Rate. By observing the NASDAQ price difference, we will predict the Unemployment Rate will rise or fall in the next month using the Hidden Markov Model. We will use the NASDAQ price and the unemployment rate from 2016 to 2020 monthly data for this paper. When we check the relation between the NASDAQ price and the unemployment rate, we find out that whenever the NASDAQ price goes up, the unemployment rate will drop for a time. So we are interested in how we can build Hidden Markov Models (HMM) by using the data we have. Furthermore, we want to see if our model is more accurate than other models that predict the unemployment rate.