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  1. I have 2 years day-wise data of stock price.
    What frequency I should take in this case for next 1 year day wise prediction?

  2. I have one day minute-wise data.
    What frequency I should take for next day forecast minute wise?

Actually I want to know what is frequency w.r.t. time series and prediction?


I have given tou a scenario : I have 2 years day wise data of stock price.what frequency I should take in this case for next 1 year day wise prediction. ie i want to convert my raw data of stock price for last two years(daily basis) and I want to convert this into a time series for ARIMA model.I want to know what value for frequency argument I should give inside ts() of R s/w. And how it is decided . Is it clear now?

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  • $\begingroup$ What are you mean say "frequency"? Timeframe? 1 hour, 1 day, 1 week, 1 month? $\endgroup$ – Nick Aug 2 '16 at 7:14
  • $\begingroup$ yes, you need to clarify $\endgroup$ – Antoine Aug 2 '16 at 7:15
  • $\begingroup$ 0 down vote accept I have given tou a scenario : I have 2 years day wise data of stock price.what frequency I should take in this case for next 1 year day wise prediction. ie i want to convert my raw data of stock price for last two years(daily basis) and I want to convert this into a time series for ARIMA model.I want to know what value for frequency argument I should give inside ts() of R s/w. And how it is decided . Is it clear now? $\endgroup$ – user125321 Aug 3 '16 at 7:28
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I assume that you have raised this question in context of frequency argument while modeling the time series using some tool, say R.

The interpretation of frequency for time series packages is generally 'the number of observations in a series if you consider the natural time interval of measurement'. For example, if you measure value of some variable once in a month, and you have data for multiple years, you can use value of 12 for frequency.

But things get tricky where there could be multiple levels of seasonality. For example, if you measure number of visitors to a web page every hour, there will be seasonality by hour as well as by day.

Bottom line is, very hard to tell you one single number purely based on information that you have given. You can study Rob J. Hyndman's blog post "Seasonal periods" for more details.

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  • $\begingroup$ Yes, This is related to Time series in R. $\endgroup$ – user125321 Aug 2 '16 at 10:08

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