Tesla is one of the most popular and talked-about companies in the stock market today. As a result, predicting the company's stock price may seem very enticing to investors. By using data science, we can provide helpful insights for investors looking to make informed decisions.
By using machine learning algorithms, we can analyze historical stock prices and predict future trends. We can also identify patterns and trends within the data along the way. This will then give a helping hand to investors looking at Tesla
Yahoo Finance. (n.d.). Tesla, Inc. (TSLA) Historical Data. Retrieved February 26, 2023, from https://finance.yahoo.com/quote/TSLA/history/?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAAfU1huCPC2LeeEGDtaLhIQjWVasH9SS7s4IZUKBFbjI8czcSsTQI5AxsT9aiArCISKmuock2qHmmJfL7I1XSoGmK55gcjMiJSSe3bJuAeLvJGPnlO4P6t-qFUflc6AwZ1t_uxeff4l0YmdY60cMSVd6W3OJ7Gikd-fX48u0FM32
We will use a Kaggle datset of Tesla Stock to analyze the following features:
import pandas as pd
pd.read_csv('TSLA.csv').head()
| Date | Open | High | Low | Close | Adj Close | Volume | |
|---|---|---|---|---|---|---|---|
| 0 | 2010-06-29 | 3.800 | 5.000 | 3.508 | 4.778 | 4.778 | 93831500 |
| 1 | 2010-06-30 | 5.158 | 6.084 | 4.660 | 4.766 | 4.766 | 85935500 |
| 2 | 2010-07-01 | 5.000 | 5.184 | 4.054 | 4.392 | 4.392 | 41094000 |
| 3 | 2010-07-02 | 4.600 | 4.620 | 3.742 | 3.840 | 3.840 | 25699000 |
| 4 | 2010-07-06 | 4.000 | 4.000 | 3.166 | 3.222 | 3.222 | 34334500 |
The data will be used to analzye the historical trends and patterns in the Tesla stock prices, and build a predictive model that can forecast future stock prices. Linear regression can be an option for machine learning that will allow us to predict future stock prices for Tesla.