I used Facebook's Prophet to predict the Dow Jones Industrial Average.

Reference link: Document

What is Prophet?

Prophet is a tool developed by Facebook to predict time series data. It seems that it is fast and fully automatic. Let's use it for a moment.

Target data

Uses the daily Dow Jones Industrial Average since 1948.

Installation

pip install fbprophet

import fbprophet
fbprophet.__version__
#'0.6'

Data import

The format must be columns = ["ds", "y"].

Create an instance of Prophet object and fit it.

m = Prophet(daily_seasonality=True)
m.fit(df)

If the frequency of time series data is not daily but hourly, set daily_seasonality = True.

Create future data frames.

future = m.make_future_dataframe(periods=365)
future.tail()

Predict.

forecast = m.predict(future)
forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()

Here, I will explain the variables -** yhat : Predicted value - yhat_lower : Lower limit of predicted error - yhat_upper **: Upper limit of predicted error

Plot.

fig1 = m.plot(forecast)

It is generally within the margin of error.

View individual elements.

fig2 = m.plot_components(forecast)

Sure, the quote says "Sell in May and go away, and come on back on St. Leger's Day." (Sell stocks in May and don't come back until St. Leger's Day (mid-September)) There is a saying. This seems to be something (laughs)

This is the basic usage, please see the document for more details.