How To Use Artificial Intelligence To Invest

Artificial intelligence (AI), once the stuff of science fiction, is now making million-dollar investing decisions in milliseconds. You may be wondering: Is AI the key to unlocking unprecedented returns, or is it a double-edged sword that could reshape the financial landscape in unpredictable ways?

Integrating AI into investment portfolios is no longer reserved for tech giants and hedge funds. However, from stock selection algorithms to machine learning models that predict market trends, AI tools have become far more available to retail investors. These technologies can process vast amounts of data, help allocate portfolios, manage risk, and even provide personalized investment advice. Yet, as these AI applications proliferate, so do the questions surrounding how well they work and their long-term impact on the market. Are we on the cusp of a new era of data-driven investing, or are we inadvertently ceding control of our financial futures to algorithms we don’t fully understand?

Below, we explore the practical applications of AI in personal investment strategies. We’ll review how everyday investors are using these tools to try to improve returns and mitigate risks.

Key Takeaways

• As artificial intelligence (AI) becomes more common and accessible, investors have begun incorporating it into how they investing strategies.
• Standard uses for AI include stock picking, portfolio construction and management, and risk management.
• Many robo-advisory companies leverage AI.
• It’s important to do your due diligence before using AI in your portfolio.

How To Use Artificial Intelligence in Your Portfolio 

Here are some of the ways retail investors are using AI in their portfolios.

Stock Picking With AI

Investors have an overwhelming amount of data on all stocks traded on U.S. markets, which they examine to decide whether specific shares are worth buying or selling. AI potentially allows you to sort through this data to identify stocks that meet their criteria.

For example, stock screeners are sophisticated tools that filter stocks based on criteria that include fundamental and technical data points, such as accounting ratios, market capitalization, trading volume, and moving averages, to name just a few of the hundreds of data points available.

If you’re looking to get started with a stock screener, consider learning how to use these platforms by starting with one of the many free versions that are available, like ZACKS (Nasdaq).

For more of the best stock screeners, see Investopedia’s Best Stock Screeners.

AI-Automated Portfolios

Robo-advisors like Wealthfront and Betterment automate the traditional process of working with an advisor to outline investing goals, time horizons, and risk tolerances to create a portfolio. Automated portfolios guide you through a questionnaire that then scores to a model portfolio that meets the criteria of the investor.

In addition to the questionnaire and the scoring of models, these platforms also use AI to determine the best mix of individual stocks for your portfolio. Automated portfolios can also be set to rebalance automatically should the target allocations in the portfolio drift too far from your original selections. 

Managing Trades With AI 

High-speed computing and near-instantaneous market trading has vastly changed how investors manage their trades in recent decades. Brokerage companies now offer customers sophisticated AI-powered order entry tools that can monitor and execute trades based on your criteria. This automated approach to trade management can significantly improve your trades.

For example, an AI-driven system can be programmed to do the following:

1. Buy a stock when it meets the conditions you set.
2. Manage exit strategies using conditional orders.
3. Carry out stop-loss orders or take-profit levels based on real-time market conditions.

A major advantage of using AI for trade management is its potential to mitigate the emotional aspects of trading. By adhering to preset rules and criteria, AI systems can help you keep disciplined and avoid impulsive decisions that can ruin your long-term strategies. This emotional detachment can be particularly valuable in volatile market conditions, where human emotions often lead to rash trading.

However, it’s crucial to remember that while AI can help manage your trades, it should be used judiciously. You still have to understand the underlying strategies and regularly review and adjust your AI trading criteria to ensure they align with your investment goals and risk tolerance.

While the Investopedia analysis of some AI-backed hedge funds (see chart above) shows so far less-than-stellar returns compared with their benchmarks, that doesn’t mean such approaches won’t be successful for those with less experience and knowledge who could use the discipline and knowledge AI-based systems can provide.

Portfolio Optimization

AI is a good tool for improving a portfolio, allowing you to identify a portfolio that fits your specific needs, including your risk tolerance and time horizon. In addition, once you select a particular type of portfolio, a platform’s AI can be used with modern portfolio theory to choose stocks and other assets that fall on the efficient frontier. This is a set of optimal portfolios that offer the highest expected return for a preset level of risk.

Below are other uses for AI in constructing a portfolio:

Managing Risk With AI

AI can optimize portfolios to lie on an efficient frontier, hopefully putting expected returns at the level of risk you’re willing to accept. These systems can also monitor and alert you when you’re overexposed to individual stocks or sectors. Here’s a look at how AI can be used to bolster classic ways of managing risk:

• Managing risks for specific trades: AI-powered tools can carry out complex order strategies, such as conditional orders, stop-losses, and take-profit levels, to manage risk on active trades. In addition, AI programs can design and automate options strategies for hedging and income generation, adjusting these strategies in real time based on market conditions.
• Sophisticated risk analysis: AI can run millions of simulations to assess portfolio risk under various market scenarios, providing a more comprehensive view of potential outcomes. It can also subject portfolios to stress tests, helping you understand how your investments might perform during market crises.
• Dynamic risk adjustment: AI systems can continuously analyze market data, news, and alternative data sources to detect risks early. Machine learning algorithms can adapt risk models in real time, accounting for changing market dynamics and correlations.
• Behavioral risk management: Algorithmic trading powered by AI can help reduce the emotional aspect of trading. AI systems can implement preset rules, helping you stick to your risk management strategies even in volatile markets.
• Regulatory compliance: AI can ensure that portfolios remain compliant with laws and regulations, as well as your mandates, automatically flagging or adjusting for potential violations.
• Tail risk management: AI models can attempt to identify potential extreme events that traditional models might miss, helping prepare for tail risks, also known as “black swan” events.

74%

The percentage of American investors in a 2023 survey who said they would trust human advice over that of AI.

How Robo-Advisors Use Artificial Intelligence

Through automated portfolio building, robo-advisors automate the traditional process of working with an advisor to outline investing goals, time horizons, and risk tolerances to create a portfolio that meets the needs of the investor.

Automated portfolios guide the user through a questionnaire that then scores a model portfolio that meets the investor’s criteria. In addition to the questionnaire and the scoring of models, these platforms also use AI to determine the best mix of individual stocks for the portfolio, which is often accomplished using modern portfolio theory. Further, automated portfolios are also set to automatically rebalance if the target allocations drift too far from the selected portfolio. 

Steps for Using Artificial Intelligence While Investing 

If you want to incorporate AI into your investing or trading, you may consider taking the steps that follow.

Step 1: Set Out Your Financial Goals

The first step is the same for every investor, which is to understand your financial goals so you can move forward with an investment strategy that fits your needs.

Step 2: Choose Your Investing Method

Next, you need to determine whether you’ll use a robo-advisor that does much of the work or invest on your own. If you go with a robo-advisor, the advisor’s AI technology will do the heavy lifting. You’ll answer questionnaires, review model proposals, and give further input on portfolio management. 

Step 3: Select an Investing Strategy

If you’re deciding on the investments, you’ll need to determine your strategy to understand the types of stocks you want. You can also use suggested models from robo-advisors, often available for free, to help determine the mix of asset classes for their portfolio. This uses AI to help set a strategy you’ll manage individually.

Here are many of the major strategies investors use and how AI can help with them:

Step 4: Identify Your Investing Tools

Stock screeners are helpful AI tools when choosing individual stocks for your portfolio. These often have preset filters to help you get started.

Step 5: Start Managing Your Portfolio

Once the portfolio is up and running, you can employ different automated tools to help manage your positions to enter and exit your positions. You might also want to refine your stock screen searches and learn to use the efficient frontier to craft a portfolio for favorable returns and the lowest risk possible. 

What Is Artificial Intelligence (AI)?

AI refers to using machines to simulate human intelligence. AI is performed by computers and software and uses data analysis and rules-based algorithms. It can entail very sophisticated applications and encompass an extensive range of applications. The tremendous amount of data available on financial markets and financial market prices provides many prospects for applying AI while trading. 

What Kind of Financial Data Is Analyzed by AI?

AI can analyze just about any financial information. This includes fundamental data, such as a company’s earnings, cash flow, and any other data that may impact the stock’s price. AI is also used in technical analysis, which incorporates data on the number of shares traded and other mathematical criteria related to past prices.

Is Investing With AI Suitable for Beginners?

Absolutely. Robo-advisors are often the first step for beginning investors, and these platforms rely heavily on AI. While some AI represents the newest technology and the ability to understand and process language, plenty of it is much more intuitive. AI allows investors to filter stocks that meet their criteria much more simply through stock screeners.

Is Investing With AI Safe?

Investing with AI often is, but it’s not without risks. AI-powered tools can provide more sophisticated risk management, better diversification, and reduced emotional bias in decisions. They can quickly process vast amounts of data, potentially identifying risks and prospects that human analysts might miss. However, AI systems are often quite fallible. They can make errors if fed inaccurate data or their algorithms are flawed. There’s also the risk of overreliance on AI, potentially leading to herd behavior if many investors use similar AI models. In addition, AI systems may not fully account for unprecedented events or market conditions.

Therefore, while AI can significantly improve investment safety, it’s crucial to use it as a tool to augment, not replace, human judgment.

Can AI Predict the Stock Market?

Whether AI can effectively predict the stock market is uncertain, but many are spending great amounts of money to find out. In a 2023 study, a machine-learning model outperformed traditional methods of predicting stock movements, earning an average return of 2.71% monthly compared with 1% using conventional methods, indicating a promising future for using AI in stock predictions. However, other efforts have failed to outperform benchmarks.

The Bottom Line

AI’s role in investing is here to stay. Even if you are not using AI yourself, portfolio and fund managers all employ AI in numerous ways, and your investment advisor could be using some of the same tools to help you with your portfolio.

If you are a hands-on, active investor, you can use AI-based platforms to manage your portfolio, make decisions on purchases and sales, and manage trading positions. As such, it’s important to understand and keep abreast of developments in the AI and investing space.