Hidden Markov Model for Stock Trading
AbstractHidden 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
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Nguyen, N. Hidden Markov Model for Stock Trading. Int. J. Financial Stud. 2018, 6, 36.
Nguyen N. Hidden Markov Model for Stock Trading. International Journal of Financial Studies. 2018; 6(2):36.Chicago/Turabian Style
Nguyen, Nguyet. 2018. "Hidden Markov Model for Stock Trading." Int. J. Financial Stud. 6, no. 2: 36.
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