AI Trading: How AI Is Used in Stock Trading

AI trading is a growing part of the fintech industry. These companies are paving the way. While humans remain a big part of the equation, artificial intelligence has taken on an increasingly significant role in trading. The global AI trading market was valued at $18.2 billion in 2023, and it could nearly triple in size by 2033.

AI Stock Trading

AI stock trading uses machine learning, sentiment analysis, and complex algorithmic predictions to analyze millions of data points and execute trades at the optimal price. AI traders also analyze forecast markets with accuracy and efficiency to mitigate risks and provide higher returns.

With AI becoming a constant presence in financial trading, we’re taking a closer look at how AI is reshaping the trading landscape, the consequences of this development, and the biggest players driving this change.

What Is AI Trading?

AI trading refers broadly to the use of artificial intelligence, predictive analytics, and machine learning to analyze historical market and stock data, get investment ideas, build portfolios, and automatically buy and sell stocks.

How AI Stock Trading Works

AI trading companies use various AI tools to interpret the financial market, use data to calculate price changes, identify reasons behind price fluctuations, carry out sales and trades, and monitor the ever-changing market. There are several types of AI trading:

1. Quantitative Trading (Quant Trading): Uses quantitative modeling to analyze the price and volume of stocks and trades, identifying the best investment opportunities. Investors often use quantitative trading to complete major transactions involving up to hundreds of thousands of shares.
2. Algorithmic Trading (Algo-Trading): Stock investors use algorithms that make decisions based on historical data to execute trading decisions. These algorithms apply machine learning and deep learning to analyze market trends and financial news before making trades in small portions.
3. High-Frequency Trading: Large quantities of stocks and shares are bought and sold rapidly. This type of trading depends on high-powered computers that can simultaneously analyze multiple markets and complete millions of trades in a few seconds, giving investors a competitive advantage.
4. Automated Trading (AI Trading): A way of executing trades using pre-programmed trading instructions. It is similar to algorithmic trading but operates on more basic trading strategies.
5. Arbitrage Trading: Exploits market differences by buying an asset in one market and selling it for a higher price in a different market. AI trading tools can monitor multiple markets at the same time, allowing investors to capitalize on these inefficiencies and generate small profits.

AI Trading Tools

Investors have many tools at their disposal when it comes to AI trading:

1. Portfolio Managers: These AI tools autonomously select assets to create a portfolio and then monitor it, adding and removing assets as needed. Investors can seek financial advice from AI managers, submitting information on their financial goals and risk tolerance to inform an algorithm’s financial decisions and advice moving forward.
2. Trading Robots: AI-powered trading robots refer to software that makes decisions based on predetermined rules it’s programmed to follow. These rules often consist of ‘if/then’ statements, enabling algorithms to complete trades only under certain conditions.
3. Signals: AI signals are pre-programmed to send automatic alerts when they discover stocks that meet specific requirements. Similar to trading robots, signals analyze stocks and act based on preset rules. Unlike trading robots, signals provide alerts without executing trades.
4. Strategy Builders: AI tools investors can train to follow their rules. Investors can backtest how their AI strategy builders could perform by having them operate within historic market conditions and simulate their strategies in action with virtual capital.

AI Trading Techniques

AI contributes to various parts of the investing process:

1. Data Mining: Compiling and analyzing massive volumes of data to identify trends and patterns. AI can gather historical data and extract insights into past stock market behaviour.
2. Sentiment Analysis: Analyzing all online financial-related activity, including discussions on social media, news platforms, community forums, and other online spaces.
3. Real-Time Analysis: Algorithms analyze data as soon as it is produced to determine market patterns and trends.
4. Predictive Modeling: Collecting past data to anticipate future trends. AI algorithms can process millions of transactions and analyze historical data to predict stock market behaviour.
5. Risk Modeling: Weighing the possibilities of different events based on historical data and analysis.
6. Stress Testing: Testing an investment strategy on historical data or through simulation to see how it holds up under various circumstances.
7. Backtesting: Testing an investment strategy using historical data before allowing an AI tool to use this strategy to conduct real-world trades.
8. Benchmarking: Evaluating an investment strategy by comparing it to a stock market benchmark or index.

Benefits of AI Trading

AI trading offers several advantages:

1. Reducing Research Time and Improving Accuracy: AI trading automates research and data-driven decision-making.
2. Predicting Patterns: Using sentiment analysis to gather information from news outlets and social media.
3. Stronger Risk Management: AI tools can automate data collection and build predictive models based on historical data.
4. Lowering Costs: AI trading technology can replicate some repetitive tasks traditionally done by humans, reducing overhead expenses.

Risks of AI Trading

While AI trading has many benefits, there are also risks:

1. Less Transparency: Humans can’t comprehend the complex calculations AI makes in trading decisions.
2. Too Reliant on Historical Data: Stock markets can be volatile, and unprecedented events could place new stress on markets.
3. Larger-Scale Errors: Software errors can cause massive trouble when multiplied on the scale of hundreds of thousands of trades.
4. Cybersecurity Concerns: AI trading tools can become targets of cyberattacks, leading to data breaches and financial instability.

Lares Algotech: Leading the Way in AI Stock Trading

Lares Algotech is one of the companies at the forefront of AI stock trading, leveraging advanced AI tools and techniques to provide cutting-edge trading solutions. Their expertise in AI-driven trading strategies, risk management, and predictive modelling sets them apart as a leader in the industry.

AI trading is revolutionizing the stock market, offering significant benefits and presenting new challenges. As technology continues to evolve, the role of AI in stock trading will undoubtedly become even more prominent, shaping the future of the financial industry.