Markov switch state probabilities forecast
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Markov switch state probabilities forecast
Hello everyone,
I need help estimating markov switch models. In particular I cannot understand how I can carry out forecast checks for probability states.
can you help me?
I need help estimating markov switch models. In particular I cannot understand how I can carry out forecast checks for probability states.
can you help me?
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- Posts: 15
- Joined: Sun Jul 28, 2019 2:26 pm
Re: Markov switch state probabilities forecast
can anyone help me?
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- EViews Developer
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Re: Markov switch state probabilities forecast
I'm afraid that I don't understand the question.
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Re: Markov switch state probabilities forecast
Simply
I need to forecast a state probability but the software it allow the forecast of only fitting series.
I need to forecast a state probability but the software it allow the forecast of only fitting series.
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- EViews Developer
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Re: Markov switch state probabilities forecast
I'm sorry, but that is correct.
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Re: Markov switch state probabilities forecast
sorry but I do not understand.
The markov model is born to return the probabilities of state, right?
so how can I carry out goodness tests of the probabilities without being able to carry out forecasts in sample and out of sample?
The markov model is born to return the probabilities of state, right?
so how can I carry out goodness tests of the probabilities without being able to carry out forecasts in sample and out of sample?
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- Non-normality and collinearity are NOT problems!
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Re: Markov switch state probabilities forecast
EViews produces several different measures of within-sample probabilities. Try Proc Make Regime Probabilities
I don't believe EViews does out-of-sample probability forecasts, but I don't think it should be hard to do.
I don't believe EViews does out-of-sample probability forecasts, but I don't think it should be hard to do.
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Re: Markov switch state probabilities forecast
sure, in fact I can extract the probabilities but how can I test the probabilities if in the "forecast" function I can only get the series fitted?
how do I test insample and outofsample without the forecast function?
how do I test insample and outofsample without the forecast function?
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- Non-normality and collinearity are NOT problems!
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Re: Markov switch state probabilities forecast
Nicotrader87 wrote:sure, in fact I can extract the probabilities but how can I test the probabilities if in the "forecast" function I can only get the series fitted?
how do I test insample and outofsample without the forecast function?
Well, the extracted probabilities are in-sample forecasts.
If you want to forecast out of sample, I believe you just take the final state probabilities and run them out in a GENR statement multiplying by the estimated transition probabilities.
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Re: Markov switch state probabilities forecast
startz wrote:Nicotrader87 wrote:sure, in fact I can extract the probabilities but how can I test the probabilities if in the "forecast" function I can only get the series fitted?
how do I test insample and outofsample without the forecast function?
Well, the extracted probabilities are in-sample forecasts.
If you want to forecast out of sample, I believe you just take the final state probabilities and run them out in a GENR statement multiplying by the estimated transition probabilities.
please for me it is very important can you make this process clearer?
maybe with a screenshot?
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- Non-normality and collinearity are NOT problems!
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Re: Markov switch state probabilities forecast
Have you tried Proc Make Regime Probabilities?
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Re: Markov switch state probabilities forecast
startz wrote:Have you tried Proc Make Regime Probabilities?
obvious but how to make the forecast? with make probabilities get only the estimate in samples.
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- Non-normality and collinearity are NOT problems!
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Re: Markov switch state probabilities forecast
If the last in sample probability is last_prob and the transition probabilities are p11 and p01, then I think you want something like
prob(T+1) = last_prob*p11 + (1-last_prob)*p01
prob(T+2) = prob(T+1)*p11 + (1-prob(T+1))*p01
etc
prob(T+1) = last_prob*p11 + (1-last_prob)*p01
prob(T+2) = prob(T+1)*p11 + (1-prob(T+1))*p01
etc
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