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Stock Price Forecasting - Part 1 - Loading the Data and Preparing it!

This is the first video in a three-part series focused on stock price forecasting in R. in this video we will: 1) load the libraries, download 5 years of stock price data for SPY ETF from Yahoo Finance. 2) Do some data cleaning and preparation Join in the discussions and more on my FaceBook Data Science group. It's packed full of great free resources, code, cheatsheets, expert advice and much more!   / 2558540907733212   in video 2 we will: 3) create a training and test set and then get the log returns or residuals. 4) create and test four arima models including multiple auto arima and custom arima models based on both the log returns and the original SPY closing price data from Yahoo Finance. In video 3 we will: 5) determine the accuracy of each of these models, not them together and then draw logical conclusions based on the results. In this video I show you primarily how to download stock data for a period of time (5 years of SPY ETF in this example). Then we select only the daily close and plot that. Next we do an auto arima and get p,d,q values from ACF / PACF test that we will use in video 2 to build the log models and arimas. This video series is a complete walk-through into stock price forecasting using r. It also has some great commentary that shows you why we need to look at time series forecasting in more from a directional perspective rather than an exact forecast amount. In the end you will see how we do this and determine where SPY will roughly go for the next 100 days based on the data and results. This knowledge is very helpful to anyone incesting or that works in finance, but in general is helpful to pretty much everyone - who wouldn't want a little data science help when it comes to their finances and/or investing? I hope you find this educational and interesting. Please do me a favor and subscribe, like and share! This way you can get notified of all the other great videos I have coming out! Thanks again and God bless!