Predict The Stock Market With Machine Learning And Python

In this tutorial, we’ll learn how to predict tomorrow’s S&P 500 index price using historical data. We’ll also learn how to avoid common issues that make most stock price models overfit in the real world.

We’ll start by downloading S&P 500 prices using a package called yfinance. Then, we’ll clean up the data with pandas, and get it ready for machine learning.

We’ll train a random forest model and make predictions using backtesting. Then, we’ll improve the model by adding predictors. We’ll end with next steps you can use to improve the model on your own.

You can find an overview of the project and the code here – .

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00:00 – Introduction
01:28 – Downloading S&P 500 price data
03:30 – Cleaning and visualizing our stock market data
04:29 – Setting up our target for machine learning
08:19 – Training an initial machine learning model
17:01 – Building a backtesting system
23:05 – Adding additional predictors to our model
28:45 – Improving our model
33:37 – Summary and next steps with the model

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46 thoughts on “Predict The Stock Market With Machine Learning And Python”

  1. If this worked you wouldn't be making youtube videos. The biggest most powerful companies in the world with unlimited computer resources are your competitors. Good luck to all that try this. Please do paper trading only for 12months beforehand.

  2. If I'm running this code today, will I be able to see the prediction for tomorrow's in the target column as 1 ( if it's going up)? For some reason, I'm not able to see it on the table. Am I missing something ? can anyone guide? thnx

  3. Buying a stock is easy, but buying the right stock without a time-tested strategy is incredibly hard. I’ve been trying to grow my portfolio of $160K for sometime now, my major challenge is not knowing the best entry and exit strategies

  4. Actually you forgot to measure the expectancy of a trade in the case it has a precision of 42%. Because what makes a strategy profitable is bit the win rate but rather the expectancy of the trades. Although it is a great video and a good tutorial about programming. Thanks and keep up the good work.

  5. Hi, I am using a dataset where I have only 1440 rows. Can I also write a piece of code that backtests this amount of data? When using these arguments (start=2500, step=250), it skips my whole data since it only has 1440 rows. What would you suggest to set start and step to?

  6. Scholars who study the stock market’s historical performance estimate that over time, the payment (and reinvestment, and compounding) of dividends have contributed anywhere from 30% to 90% of the S&P 500’s total returns. I want to spread across $400k into profit yielding dividend equities but unsure of which to get into.

  7. Vikas,

    I have a bot project to assist investors in buying and selling assets on the Brazilian stock market. However, it seems that the bot is not able to make predictions properly. Can you help me with this bot? Could you review my code? Thank you in advance!

  8. Thank you for your videos. But what if I have multiple stocks to predict, and when I parse one stock id in, I want to get the specific prediction for that id only. will it be feasible?

  9. hi, I wonder how reliable would this be if I predicted the 10, 20, or more candles into the future with an accuracy of 75 to 90 percent. do you think its gonna be useful in the financial markets. since I did create features which predicts the prices with an accuracy of 85 percent.

  10. My spouse and I are adding a variety of stocks/ETF to my present holdings for the long term, We've set aside $250k to start following inflation-indexed bonds and stocks of companies with solid cash flows, I believe it is a good time to capitalize on the market for long-term gains, but it wouldn't hurt to know means of actualizing short term profit.

  11. Bro I like your coding and respect you, but you are missing some first principles here and you need to take this video down.

    You will never beat the big fish at this game. They are infinitely better resourced than you and ANYBODY watching this. You need to accept that the stock market is and always was an insider's game, and anyone who believes they can get an "edge" over these insiders is a goddamn fool.

    Nassim Taleb wrote about this in his "Black Swan" book. It's called, "The Ludic Fallacy". You are unwittingly indulging in this with this well-intentioned video. You are not going to beat the market with your game here. Accept this.

    Now, please take this down. It is not ethical to lead the blind to perdition by making them believe that they can beat the house. They cannot, neither can you, and if you were actually smart enough to have an edge you would be working for Goldman Sachs instead of posting YouTube videos.

  12. Hi @Everyone, I am getting this following error when trying to get the predictions for the second time on the new_predictors
    Code: predictions = backtest(nifty50, model, new_predictors) FYI, I am using Nifty50 dataset.
    ValueError: Length of values (1) does not match length of index (250)
    Can anyone guide me through this error, I am not getting it. Any help would be much appreciated.

  13. Nice but unfortunately, YAHOO data is good if you are using "DAYS" as the measurement. It does not give you live data ( 1 minute or 5 minute chart which is needed by Day Traders ). Can you suggest a data source that can give you live data ?

  14. There is no predicting the future of the stock market. Do you mean to tell me this man can build a machine that will tell you what S&P 500 is going to do tomorrow? Why is he wasting his time making YouTube videos? That should answer your question. This guy should be a billionaire by now.

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