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Predicting High Frequency Financehigh frequency finance time series with HMM

Added tag "r" according to question's comments
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gung - Reinstate Monica
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I have a the following time series

  Price      BrokerID 632 Behaviour  BrokerID 680 Behaviour ...BrokerID XYZ Behaviour

  5.6          IP                       SP                   
  5.7          BP                       IP
  5.8          SP                       BP
  5.83         IP                       SP

where IP =Idle position IP is idle position, BP is buying position, and ,sellingSP is selling position  .I I want to use Broker behaviour as the known variable and price as the hidden variable and predict it using HMM  .But But my question is how to find the emission matrix between a character vector (broker behaviour) and price numeric vector?

I have a the following time series

  Price      BrokerID 632 Behaviour  BrokerID 680 Behaviour ...BrokerID XYZ Behaviour

  5.6          IP                       SP                   
  5.7          BP                       IP
  5.8          SP                       BP
  5.83         IP                       SP

where IP =Idle position , buying and ,selling position  .I want to use Broker behaviour as the known variable and price as the hidden variable and predict it using HMM  .But my question is how to find the emission matrix between a character vector (broker behaviour) and price numeric vector

I have a the following time series

  Price      BrokerID 632 Behaviour  BrokerID 680 Behaviour ...BrokerID XYZ Behaviour

  5.6          IP                       SP                   
  5.7          BP                       IP
  5.8          SP                       BP
  5.83         IP                       SP

where IP is idle position, BP is buying position, and SP is selling position. I want to use Broker behaviour as the known variable and price as the hidden variable and predict it using HMM. But my question is how to find the emission matrix between a character vector (broker behaviour) and price numeric vector?

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