How to Use AI for Investing | Tools & Predictions

Artificial intelligence has taken the world by storm recently, disrupting virtually every branch of human industry, including investing. Powerful software can now almost instantaneously process huge amounts of data and deliver invaluable conclusions about the evolving market. This detailed guide will uncover how to use AI for investing in many relevant aspects and analyze the benefits investors can gain with the right tools and predictions.

What is artificial intelligence?

It is tough to find anything without AI today. The ads you watch online are governed by a specialized algorithm. Your neighbor’s kid is fighting an AI in a video game right now. The person from the customer service you talked to yesterday? Yup, AI. Likewise, someone investing in the same market as you is using AI to analyze data that would take weeks just to read through. Like with other sectors, it is getting difficult to imagine investing without AI. 

In other words, AI can help with many things, but how exactly can you use AI for investing?

How can AI help investors make smart decisions?

AI algorithms and machine learning allow sophisticated software that deciphers data and recognizes patterns, which is further processed to produce concrete investing recommendations.

In other words, AI can help investors gain valuable insights into market movements, assess risk, and provide forecasts based on the available data and ongoing trends. Furthermore, autonomous decision-making allows investors to execute their trading strategies and manage portfolios using pre-set conditions and rules.

Resourceful investors can utilize artificial intelligence to craft better strategies, increase the speed of their decision-making exponentially, and, most importantly, gain better returns on average.

How is AI used in investing?

There are many, many ways by which AI can help investors make smarter decisions, so here we’ll give the most common ones:

• Predictive analytics. Predictive AI can identify patterns in vast amounts of market-related data and then use them to predict market trends and provide informed price movement forecasts. Similarly, this also applies to social media, news outlets, and other sources of information to produce a broad sketch of behavioral habits in a target audience;

• Portfolio management. Having a solid grasp on real-time market trends allows AI to automate portfolio management based on personal preferences (like risk tolerance, time, and investment approach) and ongoing market trends;

• Risk measuring. Speaking of risk, the AI’s ability to identify patterns also comes in handy when spotting anomalies in these trends. In other words, investors can use AI to gauge risk on the sector level and the broader market volatility but also detect potential frauds and other types of scams;

• High-frequency trading and mass-trading. Although these tactics are primarily reserved for institutional investors due to high costs and sophisticated equipment requirements, AI can be used to exploit the global market inefficiencies. For example, market self-regulation is not instantaneous, and the use of AI allows big investors to exploit fractional discrepancies on a large scale and high frequency;

• Alternative data analysis. As AI is not limited by “conventional” restrictions like time and prioritization, it can also be feed alternative data to support or disprove predicted trends, including satellite data, credit card transaction maps, and geolocation information;

• Stress simulation. AI is also quite handy in simulation, as savvy users can set extraordinary parameters and watch it behave in fringe circumstances. This ability allows the smart software to assess how portfolios and strategies react in specific scenarios, like geopolitical crises or recessions.

AI price prediction tools

The most widespread use of AI for investing is an AI price prediction tool, which is simple to navigate and provides straightforward indicators and instructions.

Simply define the inputs for the software, which can be any of the currently popular stocks or cryptocurrencies, and specify a timeframe (1 day, 7 days, 15 days, 30 days, and 60 days).

Our tool also allows you to fine-tune the parameters even further by setting the AI model and prompt version.

After you press the “Predict Price” button, simply allow the tool the time to process the data. It will promptly provide predictions and insights based on the selected models.

How to use AI for investing: 4 ways

Okay, so that was how AI  can generally benefit investing, but there are also specific investing cases with excellent AI solutions. What’s more, these tools can be used by all retail investors, including you, right now.

Stock price prediction

Using AI for stock price prediction is perhaps its most common use among retail investors. It refers to using machine learning and algorithms to assess historical data and provide market trends and specific financial indicators. That way, AI can forecast stock prices and market trends.

Artificial intelligence isn’t impervious to making mistakes, but it is still much better at this than humans. It can produce conclusions that can steer the decision-making in the right direction and reduce the overall risk that stock investors face. Stock prediction AI tools are used by virtually every stock investor, from day traders and rookies to institutional investors looking to maximize gains and minimize risks. 

Overall, AI stock market analysis tools have several benefits over human investors:

1. Speed: AI does in a fraction of a second what humans would require hours for;
2. Accuracy: Stock market AI tools are more reliable at identifying patterns;
3. Lack of emotions: Artificial intelligence is immune to emotions like fear and excitement;
4. Customization: Most of these tools allow the implementation of custom-made strategies that fit your investing style.

Specific use cases for AI for stock market prediction

Here are some key areas where AI can make a significant impact on your stock investing practice:

Application	Description	Potential benefits
Stock screening	Spots potential stock investments based on specific criteria	Simplified screening process
Day trading	AI analyzes short-term trends and suggests trades	Quick decisions, improved success rates
Portfolio management	Balancing assets for long-term growth	Optimized returns, reduced risk
Risk assessment	Identifying factors that could negatively impact performance	Minimized losses, smarter strategies
Market forecasting	Predicting long-term market trends and sector performance	Better planning, informed investment moves
Sentiment analysis	Gauging public opinion from news and social media	Early identification of market-moving events

Crypto trading

The cryptocurrency market is pretty young and volatile. Furthermore, it is open 24/7, and substantial price swings can happen overnight. As such, there are many benefits to AI tools with continuous automation and autonomy to swiftly react to protect a crypto portfolio or capitalize on any significant cryptocurrency price reshape.

The greatest benefit of AI crypto investing tools is predictive analytics. By scanning the trading volume of a token and the market sentiment toward it, the AI tool can help you decide whether to buy or to sell with minimized risk in either case.

Next, unlike a flesh-and-blood crypto trader, the AI tool is active 24/7 and can send live signals or make pre-set autonomous decisions in milliseconds even when you are not actively trading. In make-or-break situations, this omnipresence is worth its weight in dollars.

So, the benefits of AI crypto trading over its manual counterpart:

1. Speed: Once again, speed is the most crucial part of AI investing tools. Living beings take time to process information, while AI simply immediately does what’s best according to the situation;
2. Complex analysis: The crypto market has many moving parts that take time and effort to compare and contrast, which is not a problem for an AI tool;
3. Lack of emotions: As crypto is more volatile than traditional markets, it is even easier for emotions to take hold and scramble a solid investing path. Not the case with AI, though;
4. 24/7 monitoring: The AI does not tire, rest, eat or get bored. Unlike humans, it can monitor and react to new developments around the clock.

Day trading

As day trading relies heavily on speed and the ability to analyze the market quickly, there is plenty of room for AI tools to enhance the day trading process.

The most obvious use of AI tools in day trading is that machine learning can provide real-time market analysis, including chart patterns and technical indicators. The smart algorithm also executes transactions much faster than a human, and in day trading, doing things faster potentially earns more money.

Finally, the most prized ability of AI tools is that they can learn over time. Continuously learning and adapting to the changing market circumstances allows artificial intelligence to deliver more relevant information, which is then used for more informed and successful trading decisions.

In short, here are the advantages of using AI for day trading:

1. Speed. Yet once again, but in day trading, perhaps more importantly than anywhere else, speed is a vital investing factor;
2. Fast and complex analysis. AI day trading tools can receive tons of data from different sets and sources to produce relevant predictions. Here, humans simply cannot compare;
3. Scalability. In the world of day trading, fractions of a second count. AI investing tools can execute exponentially more trades at once than humans, which can be the difference between profit and loss;
4. Automation. Sophisticated AI tools can do day trading without human oversight and do it better. 

Automated portfolio management and robo-advisors

In traditional investing, you can hire a professional to manage your portfolio, which is pricey, or do the management yourself, which takes time and effort.

However, the AI revolution has invented a solution to this dilemma that is neither expensive nor effort-intensive, called automated portfolio management. 

Robo-advisors and other automated portfolio managers streamline the traditional portfolio management process and provide a basis for autonomous decision-making that does not require direct orders.

That said, you still have the final word on how the portfolio manager will “behave” as you are the one who defines the investing goals, sets the periods, and declares the level of risk tolerance, usually in the form of a questionnaire.

Artificial intelligence has many uses in automated portfolio management, as it can apply its exhaustive analytical prowess to determine the best individual stock/crypto/securities ratio for your preferences. 

Let’s go through the advantages of using AI-powered robo-advisors:

1. Efficiency. Robo-advisors and automated portfolio managers provide the expertise of a financial expert for a fraction of the cost you would spend on them;
2. Asset allocation. AI tools are proficient at analyzing diverse factors and can, therefore, provide informed directions for your asset allocation;
3. Risk optimization. Due to a deep survey of multiple risk-related factors, these tools can accurately gauge the risk that you are willing to expose your portfolio to;
4. Automation. If set correctly, AI-powered robo-advisors and automated portfolio managers can work exceptionally well in the long term with minimum interference and monitoring.

Can AI beat the market?

It is notoriously hard to beat the market. In fact, Finbold’s previous inquiry into this question yielded that less than 4% of institutional investors survived into their fifth year, which means that more than 95% of investors fail in the long run.

Many agree that the best way to “beat the market” is just to invest in the broader economy (exemplified in the S&P 500 index) and have several years of patience.

However, would the answer be different if we included AI?

The answer is a mixed bag. First of all, AI tools still cannot predict the future. They are better at coming to data-based conclusions than living retail investors, but they are still far from a 100% success rate. In fact, 2022 research showed that better stock prediction abilities do not guarantee that AI will have the ability to beat the market by itself. 

A 2021 paper shows that a trained AI analyst beats most human analysts (54.5%) but that humans beat AI when institutional knowledge is crucial, such as intangible assets or financial troubles. The research concluded that AI and humans exhibit complementary abilities: AI tools are better at processing large volumes of data and identifying patterns. In contrast, humans’ ability to contextualize insight helped steer the decision on the right path.

4 mistakes to avoid in AI investing

AI is a powerful investing tool, but it is still prone to mistakes and requires human guidance. You should constantly critically evaluate the decisions made by your intelligent software. Here’s why:

1. AI is limited. AI’s judgment is bound to historical data and inherent biases and lacks a human understanding of particular market contexts. If not properly guided, it will make mistakes;
2. Misalignment of goals. Your investing objectives and those of your AI tool may not always align. Do not follow through with your AI’s advice if you do not fully understand its logic;
3. Algorithmic bias. Due to the way it’s trained, AI is prone to inheriting certain biases, leading to skewed recommendations that unduly favor specific instruments, sectors, and industries;
4. Mass-AI use. If the use of AI becomes sufficiently widespread, it will lead to systemic weak spots and market distortions.

The best use of AI comes with critical thinking, sufficient monitoring, and supporting AI’s decisions with your own research.

How does using AI for investing affect the market in the long run?

If we increasingly use AI for investing, the markets will be faster and more efficient, but the downside is greater volatility during market turmoil, a study by IMF shows. 

Institutional investors like investment banks and hedge funds have used mass-trading approaches and automated trading for decades. These algorithms made the markets more dynamic and efficient but also led to major “flash crash” events in brief periods of time.

The IMF finds evidence for this in AI-driven exchange-traded funds (ETFs), which display significantly higher (over 40 times!) turnover rates than other ETFs. These AI ETFs still claim a relatively minor portion of the market, but if they grow in numbers, they can increase the potential of herd-like panic selling during financial crises. However, financial AI experts might come up with a solution by then.

Liquid assets, including stocks and government bonds, are particularly suitable for AI investing, although the study shows that a human overseer will have to sit behind the steering wheel for the foreseeable future.

Furthermore, if retail investors’ use of AI for investing becomes widespread, it will lead to the democratization of investing. In other words, institutional investors will no longer be the dominant investing force in the market. 

Lastly, we should not ignore potential regulatory challenges regarding market transparency and fairness, as well as the potential impact on the roles of humans in the investing process, which will drastically change if AI turns out to be outright superior to humans when it comes to investing.

How to choose the best AI stock prediction tool?

The best AI investing tool depends on various factors, including your investing style and personal preferences.

1. Define your investing personality

For starters, you should outline your investing style and define your preferred asset, optimal timeline, risk tolerance, and investing approach.

Asset	Investment type and span	Risk
Stocks	Active, long- and short- term	Medium-high
Index funds and ETFs	Long-term growth	Low-medium
Cryptocurrency	Alternative, usually short-term	Very high

Naturally, your preferred AI investing tool should match your personal investing style.

2. Define the core features of the AI tool

It goes without saying that you need to find out what your tool does and how it analyzes the market.

• Make sure that your preferred AI tool relies on solid and diverse information for its predictions;
• An ideal prediction should rely on both technical and fundamental analysis to deliver its conclusions;
• The best AI tool should have customizable preferences for criteria like risk tolerance, personal objectives, and additional preferences (like ESG investing);
• It is crucial that the AI tool is safe and secure without violating your privacy or putting your personal details in danger;
• Lastly, the pricing should be transparent, with straightforward costs and fees that reflect the usability of the intelligent software.

3. Confirm upon which large language model (LLM) your AI tool is based

Artificial intelligence is rapidly evolving, with newer AI models vying for supremacy on the market with innovation, new features, more comprehensive data sets, and quicker data analysis.

What’s new today will be a thing of the past in a year or two. Additionally, some LLMs work better within different domains: some are quicker, others more detailed, and some specialize in niche tasks, while others act as your preferred jack-of-all-trades.

Consider using an AI tool that is transparent on how it provides users with results. Knowing the strong and weak sides of an LLM should help you determine how viable your AI market predictions will be.

Tips and tricks on how to use AI for investing

There’s no ultimate guidebook on using AI for investing, but we do have a list of tips you should follow to maximize its benefits:

• Define clear goals. AI works best with clear instructions. Provide a set timeline, pick your preferred market and security, and provide a realistic risk tolerance for the best results;
• Be aware of AI’s limits. AI investing tools help spot patterns and recognize trends, but they cannot predict the future. Furthermore, they are prone to inherent biases, so always double-check the results and support them with your own research;
• Diversify with traditional investments. Entirely relying on AI can have serious consequences in an over-optimized market in case of high volatility. To evade herd-selling crashes, maintain a healthy ratio of AI and non-AI investments;
• Keep up with new AI models. Make sure that you know which LLM powers your AI investing tool;
• Monitor your AI investments. AI tools work best with a skilled human guiding its decision-making;
• Leverage automation. Automation is one of the best perks of AI, so make sure to automate mundane tasks, such as portfolio management, and make use of real-time alerts;
• Test with small investments first. Do not go all-in before you fully grasp the capabilities of your AI investing assistant.

Disclaimer: The content on this site should not be considered investment advice. Investing is speculative. When investing, your capital is at risk.

FAQs about how to use AI for investing

Can I use AI for investing?

Yes, AI can help in investing as it can quickly and efficiently analyze vast amounts of data and produce insights and predictions that can potentially increase your returns and minimize risks.

How does AI help in investing?

Investors can use AI to make better strategies, enhance their decision-making, and gain better returns on average.

Can AI make reliable market predictions?

AI tools excel at analyzing data and spotting patterns that can make accurate guesses about the upcoming market trends. That said, no AI tool is 100% correct, as the market is far too complex and unpredictable. 

What is the best tool for AI investing?

The best AI investing tool depends on your preferences and investment objectives, but we suggest you try our Finbold AI Price Prediction tool.