The stock trading apps generated a total revenue of $20.6 billion, with Robinhood having the highest revenue among all the stock trading apps that provide zero commission on the stock exchange.
There are various stock trading app companies using AI such as Robinhood for stock trends, eToro for trading strategies, and more. In this blog, we will inform you about the 15 use cases of AI in Stock trading. So, let’s get started:
How Top Stock Trading Apps Are Using AI?
Almost every stock trading app is using AI nowadays, either to suggest stocks, predict the outcome of stocks, or even automate customer support. Here are the top 3 stock trading apps that portray the use cases of AI in stock trading.
Robinhood
To enhance the customer experience in their store Robinhood leverages AI to provide insights on stock trends, predict market movements, and offer personalized investment recommendations. AI models analyze user behavior to tailor notifications and educational content to users which reduces customer churn rate on its platform.
eToro
Known for its social trading features, eToro uses AI to analyze market trends, identify investment opportunities, and enhance its CopyTrader feature, which allows users to mimic top-performing traders.
This helps them to grow their portfolio and get the best out of their ideas.
Zerodha
Zerodha’s Streak platform uses AI to automate the backtesting of strategies and algorithmic trading. Users can set trading parameters without coding, making it user-friendly for beginners looking to execute complex trading strategies.
15 Use Cases Of AI In Stock Trading
Here are all the ways by which you can use AI in stock trading to enhance customer experience, create a secure environment, automate customer support, and more. Being a leading Finance app development company, we analyzed all the possible ways by which AI can be used in a stock trading app. So, let’s dive in and check the content of this post:
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Predicting Stock Market Using Machine Learning
With the help of Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines (GBMs) in machine learning we can train the AI to read a large set of historical data which can be used to predict future moment in stocks.
With the help of our AI engineers, we can also incorporate macro and microeconomic factors, geopolitical events that can affect stock prices, and real-time market events that enable users to make informed decisions. AI enhances data prediction accurately which benefits users planning to invest heavily in stocks.
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