Using the random forest and time series analysis in r, predict stock prices.
statistics
Description
Objective: Using the random forest and time
series analysis in r, predict stock prices. You can use any one month of
data between 2015-2020 to predict stocks.
Output: PowerPoint summary report generated
from R output.
Data:
•
Use
the National Association of Securities Dealers Automated Quotations (NASDAQ)
historical data for a period of five years: 6/2/2015 – 6/1/2020. Forecast using
the closing value of the stock prices.
•
When
collecting the data, use the following uniform resource locator (URL) to obtain
historical values from NASDAQ. Interchange the stock symbols for the stocks you
are going to evaluate, like “FISV” in this example: o
https://www.nasdaq.com/api/v1/historical/FISV/stocks/2015-06-02/2020-06-01 o
Read the URL into R as a comma-separated value file, for each stock assigned.
•
The
stocks to evaluate are:
o
SBUX;
Starbucks Corporation
o
DRI; Darden
Restaurants, Inc.
o
PZZA; Papa
Johns International, Inc..
