How Machine Learning can Influence the Stock Markets?

Artificial intelligence and Machine Learning have become known names in the field of technology. They find applications in almost all the sectors. Be it manufacturing, healthcare, banking and finance, animal husbandry and many more. Machine Learning is helping various sectors to improve their operations. The stock market is not an exception.

Machine Learning has influenced and it further will be influencing the stock market for the betterment. Machine Learning as a service is improving market transactions by accurate prediction, helping in decision making and reducing the risk factors etc. But let us first acquaint ourselves with the basics of Machine Learning. Machine Learning is a sub-branch of artificial intelligence. Let us discuss these two terms before delving deep into the topic.

Artificial Intelligence

Artificial Intelligence

Artificial intelligence is the science of making intelligent machines. It is a branch of computer science that gives the power of reasoning, decision making, problem-solving and perception to the machines. Artificial intelligence is a vast concept and many technologies come under its hood. Like machine learning, deep learning, natural language processing etc. In this article, we will confine ourselves to machine learning only.

Machine Learning

Machine Learning

As already stated, machine learning is the sub-branch of artificial intelligence. Machine learning helps in training the machines. Machines are fed with a huge amount of data, examples and trained to perform tasks based on the input data. In simple words, Machine learning enables machines to perform tasks autonomously without human intervention. They also have the ability to learn from experience and they get improved over time. Some real-life examples of machine learning are Apple’s Siri, Google assistant, Amazon’s recommendation system etc.

Now we will discuss how machine learning can influence the stock market.

Also Read: Machine Learning Algorithms for Trading

Stock markets are complex as it is dependent upon various parameters like government policies, crude oil prices, GDP, current account deficit and many more. General masses have little or no idea about the working and terminologies of the stock market. This makes predicting stock markets even more complex. Machine learning applications in stock markets have helped in easing the process by assisting the general masses in the trading process. Following points shows how it can influence the stock markets.

  1. Boosting the Trading Speed

Stock market trading involves buying/selling of stocks in accordance with the price fluctuations. This process is time taking as traders have to take into account various parameters before placing orders. Handling such huge amount of data is difficult for humans. Moreover, the tendency to commit mistakes also increases. Machine learning algorithms have improved the trading speed by up to 5 percent. Machine learning algorithms can learn from past data and handle order placement autonomously. This has made high frequency trading possible.

  1. Machine Learning based Advisor Bots

One of the major influence that machine learning applications are going to make is the advisor bots. These bots will help the traders by advising them when to buy, hold or sell the stock. They also advise in which stock you should invest so as to gain the maximum returns. Advisor bots will also ensure that the processed information about market conditions is available at a single place.

  1. Predicting the unpredictable

One thing can be predicted about the stock market, It is unpredictable! The stock market is highly unpredictable as it is dependent on the huge amount of external factors. They can be national level or international level. Stock market prices fluctuate every second and it is very difficult to predict them. Machine learning companies along with stock market traders are building softwares that can predict the stock market behavior to a great precision. This will give traders ample time for the judgment of stock market and predicting its behavior well before.

  1. Cybersecurity

The introduction of online trading in the stock market has made life easier for the traders. But on the other hand, it has also opened the doors for the hackers and cybercriminals to steal the important and confidential information. Moreover, as trading is purely based on money transfers, the risk of fraudulent activities doubles. Machine Learning applications in stock markets have made online trading safer than never before by introducing multi-level security, biometrics, face recognition, and two-way authentication. Further research will improve the security to many folds.

  1. Handle Big Data

One thing you will find in abundance in Stock Market is ‘Data’. The stock market is generating a huge amount of data every day. The data you are going to handle tomorrow will be definitely more than the data you are handling today. In technical terms, this is known as ‘Big Data’. Humans have their own limitations. It is not possible for humans to handle that much amount of data. You have to make correlations and find the patterns in the data that are invisible and hard to find. Machine learning algorithms handle tonnes of data simultaneously and provide better insight of the stock market in the form of graphs, charts, and tables.

Also Read: Quantitative Trading for Absolute Beginners


In this article, we discussed how machine learning as a service can influence the stock market. Machine learning is going to make the trading process speedy and easier for the common man as well as for the big businesses. Machine Learning algorithms can also reduce the risk factors involved in the trading. In this way, if the human judgment is incorporated with machine learning algorithms, stock market operations will improve considerably.

About the Author:

I am Mandeep Kaur, working as a Data Scientist in Webtunix Solutions Private Limited. I am very enthusiastic to learn about Machine Learning and Deep Learning techniques. I always like to share my knowledge to beginners who want to start their career as a Data Scientist.

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