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regimes and stock prices. In this paper, we introduce the application ofHMMin 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 … determine an optimal number of states for the HMM. The selected four-state HMM is then used to predict monthly closing prices of …
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financial market predictions. In this paper, we use HMM for stock selection. We first use HMM to make monthly regime predictions …
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Hidden Markov model (HMM) is a powerful machine-learning method for data regime detection, especially time series data. In this paper, we establish a multi-step procedure for using HMM to select stocks from the global stock market. First, the five important factors of a stock are identified and...
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estimate the expected duration of the asset returns in states classified as rising (positive) (....), falling (negative) state … 4 days, while that of zero regime is 12 days, within any trading month of the study period (August 2005-Jnauary 2012 … asymmetric effects in the bank’s returns. The findings further reveal a minimum trading cycle of 7 days in February and a maximum …
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