Can AI invest for You? AI Investing 101 & Critical Mistakes to Avoid

Artificial intelligence is already automating mundane tasks and streamlining the rest to make our activities more manageable. With AI investing tools, enormous quantities of financial data can be processed quickly to produce clear indicators and actionable strategies. However, can AI invest for you? This guide will explain how to use AI in investing properly and which mistakes you should avoid when investing with AI. 

How is AI used in investing?

Using large language models (LLMs), AI can analyze vast amounts of information and recognize recurring patterns indicating ongoing and future market trends. Regarding investing, AI can deliver vital insights about price movements and potential investing risks.

Furthermore, smart investing tools rely on automation and autonomous decision-making, which can significantly reduce the time and effort spent on investing. These tools also perform transactions in a fraction of the time it takes humans to register the digits on their screens. 

Here are some examples of applied AI investing:

• Price prediction. AI’s ability to predict comes from its analysis of market-related data. By spotting patterns in financial information, social media, and informative outlets, AI can predict specific patterns in market trends and customer behavior;

• Risk management. Likewise, AI’s pattern-seeking capabilities come in handy with spotting irregularities and discovering potential risks, market volatility, and fraud;

• Portfolio management. Real-time market trends allow AI tools to automate and adjust portfolio management based on personal taste (like agreeable level of risk, time, and investment style) and the current economic context.

How to use AI tools for price prediction

The most common use of AI for investing is AI price prediction tools, which are easy to use and offer straightforward trading directions based on exhaustive market data analysis.

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

FInbold’s tool also allows for additional customization of parameters by opting between various AI models and prompt versions:

1. v0.1 Technical analysis model: Using indicators and macro factors to generate daily price targets with explanations;

2. v0.1.1 Technical analysis-based price prediction model: Generates daily price targets with reasoning for any market instrument;

3. v0.1.2 Simplified price prediction model: returns only JSON output with price target and brief reasoning.

Afterward, press the “Predict Price” button and wait for the tool to process the data. The process takes seconds and provides predictions and insights based on the selected models.

Can AI invest instead of you?

It is pretty challenging to beat the market. Finbold’s report shows that less than 4% of institutional investors survived past their fourth year. In other words, over 95% of institutional investors fail in the long run.

Most passive investors believe that the best way to “beat the market” is to simply invest in the broader economy (exemplified in the S&P 500 index, or SPY) and have several years of patience.

So, can AI do better?

The answer is, well, a bit complex. First of all, AI investing tools cannot predict the future. Despite being better at reaching data-based conclusions than non-artificial retail investors, they are still far below a 100% success rate. A 2022 research pointed out that better stock prediction abilities do not guarantee that AI can beat the market by itself. 

Furthermore, a 2021 paper shows that a properly set-up AI tool beats 54.5% of human investors (54.5%) but that people tend to outperform AI when contextual and institutional knowledge is crucial, e.g., intangible assets or financial troubles. The research concluded that AI and humans possess complementary abilities: AI tools are better at processing large volumes of data and identifying patterns. On the other hand, humans’ ability to contextualize insight helps make the right investing decision.

5 critical mistakes to avoid in AI investing

Artificial intelligence can be a game-changing investing tool, but it is not infallible and requires informed human guidance. Investors should constantly re-evaluate the decisions made by their intelligent software to avoid the most common mistakes with AI investing:

1. Artificial intelligence is still limited. AI’s judgment is bound to historical data. It also lacks a human understanding of particular markets and financial and real-life contexts. Always get familiar with the logic of an AI decision before investing;
2. Misalignment of goals. Your investing goals and those of AI tools are not always in accord. Consider familiarizing yourself with how AI tools work, including how machine learning deduces based on historical data;
3. Algorithmic bias. Due to the way it’s trained, AI logic has inherited certain biases, potentially leading to subjective recommendations that unreasonably 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;
5. Using AI because of trends. Only use AI investing tools if you know how they operate and deliver their results. Using AI in investing just because “everything is better with AI” might deliver worse results.

The bottom line

AI cannot invest instead of you. However, it can significantly boost your investing process by making actionable decisions using machine learning on vast amounts of financial data.

In other words, AI investing tools work best as a supplement to your standard investing approach. After all, AI is still a tool, and if you use it right, it might be the best investing tool we have.

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

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