Next Article in Journal
Measuring the Efficiency in the Lithuanian Banking Sector: The DEA Application
Next Article in Special Issue
How Macro Transactions Describe the Evolution and Fluctuation of Financial Variables
Previous Article in Journal
An Empirical Investigation of Risk-Return Relations in Chinese Equity Markets: Evidence from Aggregate and Sectoral Data
Previous Article in Special Issue
Dynamic Relationships between Price and Net Asset Value for Asian Real Estate Stocks
Article Menu

Export Article

Open AccessFeature PaperArticle
Int. J. Financial Stud. 2018, 6(2), 36;

Hidden Markov Model for Stock Trading

Department of Mathematics & Statistics at Youngstown State University, 1 University Plaza, Youngstown, OH 44555, USA
Received: 5 November 2017 / Revised: 10 March 2018 / Accepted: 21 March 2018 / Published: 26 March 2018
(This article belongs to the Special Issue Financial Economics)
Full-Text   |   PDF [452 KB, uploaded 27 March 2018]   |  


Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application of HMM in trading stocks (with S&P 500 index being an example) based on the stock price predictions. The procedure starts by using four criteria, including the Akaike information, the Bayesian information, the Hannan Quinn information, and the Bozdogan Consistent Akaike Information, in order to determine an optimal number of states for the HMM. The selected four-state HMM is then used to predict monthly closing prices of the S&P 500 index. For this work, the out-of-sample R OS 2 , and some other error estimators are used to test the HMM predictions against the historical average model. Finally, both the HMM and the historical average model are used to trade the S&P 500. The obtained results clearly prove that the HMM outperforms this traditional method in predicting and trading stocks. View Full-Text
Keywords: hidden Markov model; stock prices; observations; states; regimes; predictions; trading; out-of-sample R2; model validation hidden Markov model; stock prices; observations; states; regimes; predictions; trading; out-of-sample R2; model validation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Nguyen, N. Hidden Markov Model for Stock Trading. Int. J. Financial Stud. 2018, 6, 36.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Int. J. Financial Stud. EISSN 2227-7072 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top