Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models

  title={Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models},
  author={Lennart Oelschlager and Timo Adam},
  journal={Statistical Modelling},
Financial markets exhibit alternating periods of rising and falling prices. Stock traders seeking to make profitable investment decisions have to account for those trends, where the goal is to accurately predict switches from bullish to bearish markets and vice versa. Popular tools for modelling financial time series are hidden Markov models, where a latent state process is used to explicitly model switches among different market regimes. In their basic form, however, hidden Markov models are… 
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