-based methodology to defining market states and making asset allocation decisions with respect to both current and future state …, and covariance. The transitional dynamics of the derived states are modeled as a Markovian process. Asset weighting and …

-based methodology to defining market states and making asset allocation decisions with respect to both current and future state …, and covariance. The transitional dynamics of the derived states are modeled as a Markovian process. Asset weighting and …

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 ofHMMin trading stocks (with S&P 500 index being an … determine an optimal number of states for the HMM. The selected four-state HMM is then used to predict monthly closing prices of …

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 ofHMMin trading stocks (with S&P 500 index being an … determine an optimal number of states for the HMM. The selected four-state HMM is then used to predict monthly closing prices of …

of their high variability and unpredictable nature. A hidden Markov model (HMM) was built to analyze irrigation decision … the hidden states for the model. The paper evaluates data from the Canal B region of the Lower Sevier River Basin, near …