Closed Mohan16071996 closed 4 months ago
Can you please respond as soon as possible?
Hi,
You should specify the frequency parameter:
fcst_df = nixtla_client.forecast(df, h=24, level=[80, 90], freq='D')
See also this tutorial
You might then also want to change the forecast horizon (otherwise it will forecast 24 days ahead....)
Hope this helps.
Thanks for your reply. I have used the following configuration now.
fcst_df = nixtla_client.forecast(train, h=business_days, freq = 'B' , time_col = 'ds', target_col='Close', add_history=True,level=[80, 90])
What is the maximum horizon that the model can predict accurately. If I try to predict for one year, it gives very bad forecasts. Can you please help with this? I guess, the issue is because, model is written for hourly forecast?
In the documentation, there is a tutorial on long-horizon forecasting. Thus, you can use a different model when making long-horizon forecasts.
That said, it seems like you try to predict stock prices, which is a non-sensical forecasting task for such a long horizon. It's like trying to predict a random walk. It makes no sense. So results will (obviously) be bad.
@Mohan16071996 Is your issue resolved?
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I have data with daily format, not on hourly format.
how to handle this ?
Dataframe example:
Can you give sample code like this: fcst_df = nixtla_client.forecast(df, h=24, level=[80, 90])
4. Plot your results (optional)
nixtla_client.plot(df, fcst_df, time_col='ds', target_col='y', level=[80, 90])
If it is in daily format, how long can we forecast using this?