Apple has just announced the date of its September event when it is about to launch the new iPhone 13. It is currently the center of attention on the stock market. Stock market analysis is one of the popular applications of machine learning because we can predict stock prices using machine learning. So if you want to learn how to predict the stock prices of Apple with machine learning, this article is for you. In this article, I will walk you through the task of Apple stock price prediction with machine learning using Python.
Apple Stock Price Prediction
The September event of Apple is one of the favourite events for all Apple users, as iPhones are mainly launched during the September event. It is therefore announced by Apple that they are set to launch the new iPhone 13 on September 14. So many stock market investors can find this as an opportunity to buy Apple stock, because every time a company comes up with an innovative product, it leads to an increase in its stock price. So with that in mind, we can say that this is the best time to analyze Apple’s stock prices.
For the Apple stock price prediction task, you need to download an Apple stock price dataset. To download a dataset for this task, follow the steps mentioned below:
- Visit Yahoo Finance
- Search for Apple or AAPL (it’s the stock symbol of Apple)
- Then click on Historical data
- And at last click on download
After these steps, you will see a CSV file in your download folder. Now, in the section below, I will walk you through the task of Apple Stock Price Prediction with Machine Learning using Python.
Apple Stock Price Prediction using Python
Let’s start the task of predicting the stock prices of apple by importing the necessary Python libraries and the dataset:
Date Open High ... Close Adj Close Volume 0 2020-09-08 113.949997 118.989998 ... 112.820000 112.098999 231366600 1 2020-09-09 117.260002 119.139999 ... 117.320000 116.570236 176940500 2 2020-09-10 120.360001 120.500000 ... 113.489998 112.764717 182274400 3 2020-09-11 114.570000 115.230003 ... 112.000000 111.284241 180860300 4 2020-09-14 114.720001 115.930000 ... 115.360001 114.622765 140150100 [5 rows x 7 columns]
Now let’s visualize this stock price data to get a clear picture of the increase and decrease of stock prices of apple:
Now let’s have a look at the correlation between the features in this dataset:
print(data.corr())
Open High Low Close Adj Close Volume Open 1.000000 0.994551 0.993183 0.986214 0.986177 -0.466464 High 0.994551 1.000000 0.992951 0.993586 0.993307 -0.440943 Low 0.993183 0.992951 1.000000 0.993915 0.994187 -0.517453 Close 0.986214 0.993586 0.993915 1.000000 0.999899 -0.489536 Adj Close 0.986177 0.993307 0.994187 0.999899 1.000000 -0.493909 Volume -0.466464 -0.440943 -0.517453 -0.489536 -0.493909 1.000000
Now let’s move to the task of predicting Apple stock prices. Here I will be using the autots library in Python to predict the stock prices of apple for the next 5 days. If you have never used it before, then you can easily install it, by using the pip command:
- pip install autots
Now below is how you can predict the stock prices of apple:
Close 2021-09-08 157.595000 2021-09-09 158.491248 2021-09-10 157.846256 2021-09-13 158.758755 2021-09-14 159.934376
So this is how you can use machine learning for predicting stock prices.
Summary
So this is how you can predict the stock prices of Apple with machine learning by using the Python programming language. Stock market analysis is one of the popular applications of machine learning because we can predict stock prices using machine learning. I hope you liked this article on Apple Stock Price Prediction with Machine Learning using Python. Feel free to ask your valuable questions in the comments section below.
