In this
paper, we will illustrate the use and power of Hidden Markov models in
analyzing multivariate data over time. The data used in this study was obtained
from the Organization for Economic Co-operation and Development (OECD.Stat database url: https://stats.oecd.org/) and
encompassed monthly data on the employment rate of males and females in Canada and the
United States (aged 15 years and over; seasonally adjusted from January 1995 to
July 2018). Two
different underlying patterns of trends in employment over the 23 years observation period were
uncovered.
References
[1]
The Organization for Economic Co-Operation and Development (OECD).
https://stats.oecd.org/
[2]
Walker II, M. (2011) Hidden Markov Models for Heart Rate Variability with Biometric Applications. All Theses and Dissertations (ETDs).
[3]
Laverty, W.H., Miket, M.J. and Kelly, I.W. (2002) Application of Hidden Markov Models on Residuals: An Example Using Canadian Traffic Accident Data. Perceptual and Motor Skills, 94, 1151-1156. https://doi.org/10.2466/pms.2002.94.3c.1151
[4]
Laverty, W.H., Miket, M.J. and Kelly, I.W. (2002) Examination of Residuals to Vancouver Crisis Call Data by Using Hidden Markov Models. Perceptual and Motor Skills, 94, 548-550. https://doi.org/10.2466/pms.2002.94.2.548
[5]
Bhar, R. and Hamori, S. (2004) Hidden Markov Models: Applications to Financial Economics. Springer, Switzerland.
[6]
Lihn, S. (Forthcoming) Hidden Markov Model for Financial Time Series and Its Application to S & P 500 Index. Quantitative Finance.
[7]
Nootyaskool, S. and Choengtong, W. (2014) Hidden Markov Model Prediction of Foreign Exchange Rate. International Symposium on Communications and Information Technology, Incheon, 24-26 September 2014.
[8]
Xuan, T. (2004) Autoregressive Hidden Markov Model with Application in an El Nino Study. MSc. Thesis, University of Saskatchewan, Saskatoon.