Stock Market Prediction using Machine Learning in 2025

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What is the Stock Market?

A stock market is a public market where you can buy and sell shares for publicly listed companies. The stocks, also known as equities, represent ownership in the company. The stock exchange is the mediator that allows the buying and selling of shares. 

Importance of Stock Market

• Stock markets help companies to raise capital.
• It helps generate personal wealth.
• Stock markets serve as an indicator of the state of the economy.
• It is a widely used source for people to invest money in companies with high growth potential.

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Stock Price Prediction

Stock Price Prediction using machine learning algorithm helps you discover the future value of company stock and other financial assets traded on an exchange. The entire idea of predicting stock prices is to gain significant profits. Predicting how the stock market will perform is a hard task to do. There are other factors involved in the prediction, such as physical and psychological factors, rational and irrational behavior, and so on. All these factors combine to make share prices dynamic and volatile. This makes it very difficult to predict stock prices with high accuracy. 

Understanding Long Short Term Memory Network

Here, you will use a Long Short Term Memory Network (LSTM) for building your model to predict the stock prices of Google.

LTSMs are a type of Recurrent Neural Network for learning long-term dependencies. It is commonly used for processing and predicting time-series data. 

From the image on the top, you can see LSTMs have a chain-like structure. General RNNs have a single neural network layer. LSTMs, on the other hand, have four interacting layers communicating extraordinarily.

LSTMs work in a three-step process.

• The first step in LSTM is to decide which information to be omitted from the cell in that particular time step. It is decided with the help of a sigmoid function. It looks at the previous state (ht-1) and the current input xt and computes the function.
• There are two functions in the second layer. The first is the sigmoid function, and the second is the tanh function. The sigmoid function decides which values to let through (0 or 1). The tanh function gives the weightage to the values passed, deciding their level of importance from -1 to 1.
• The third step is to decide what will be the final output. First, you need to run a sigmoid layer which determines what parts of the cell state make it to the output. Then, you must put the cell state through the tanh function to push the values between -1 and 1 and multiply it by the output of the sigmoid gate.

With this basic understanding of LSTM, you can dive into the hands-on demonstration part of this tutorial regarding stock price prediction using machine learning.

12. Plotting the Actual and Predicted Prices for Google Stocks.

As you can see above, the model can predict the trend of the actual stock prices very closely. The accuracy of the model can be enhanced by training with more data and increasing the LSTM layers.

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Conclusion

The stock market plays a remarkable role in our daily lives. It is a significant factor in a country's GDP growth. In this tutorial, you learned the basics of the stock market and how to perform stock price prediction using machine learning. 

Do you have any questions related to this tutorial on stock prediction using machine learning? In case you do, then please put them in the comments section. Our team of experts will help you answer your questions.

If you are interested in learning further about Machine Learning, including the various ML applications across industries, do explore Simplilearn’s Post Graduate Program in AI and Machine Learning in partnership with Purdue University, and in collaboration with IBM. This comprehensive 12-month program covers everything from Statistics, Machine Learning, Deep Learning, Reinforcement Learning, to Natural Language Programming and more. You get to learn from global experts and at the end of the program walk away with great endorsements from industry and academic leaders and a skillet that is today the most in-demand in organizations across the world.

Happy learning!