The Power of AI in Stock Investing: Hope for the Future or Empty Promises

The world of stock investment is a place where literally every decision counts - even the smallest move can determine significant success or devastating failure. Making the right decisions can't be a matter of luck or chance - it relies on analyzing tons of data and a bias free approach. That's why traders are eager to reach for tools that automate their daily work, such as Scrab.com.

Let's agree, though - the very phrase artificial intelligence (AI) is a trend of sorts lately. It has entered the life of almost every industry, improved the everyday life of an average Smith, and won the hearts of people with self-driving cars, modern health care, product recommendations, and natural language processing used in marketing or the ability to (re)create images and sound. So it's no wonder that artificial intelligence is a technological change being implemented in the stock market as well - not only to automate the repetitive tasks.

In today's post, we look at how AI technology and machine learning are affecting the markets and trading strategies. Read our text - feel invited to a short tour of market trends and the battle between investors' human intelligence and neural networks!

Impact of Artificial Intelligence (AI) on Investment Decisions

To better understand the scale of today's topic, let's take a closer look at a bunch of facts. According to data compiled by Finbold, the AI market is worth as much as $207.9 billion in 2023. And this is not the last word from the industry dealing with this relatively new technology - by 2030, the value of the market will grow to a dizzying amount of $1.87 trillion.

And no wonder - as data collected by Forbes and The Economist, among others, show, most users value AI the most for making work more efficient or improving the use of big data.

Artificial intelligence cannot be denied the enormity of its capabilities and its significant impact on the technological revolution of recent years. AI focuses on data collection, analyzing complex patterns, trends, and learning on the fly from the gathered information.

Machine learning discovers correlations, based on historical data, predicts market movements, and can assess potential investment risks, with remarkable accuracy. It is used by bots highlighting opportunities that even a trained human eye might simply miss. At the same time, machine learning models are devoid of human emotions, which makes them potentially a good advisor.

The financial sector itself is implementing AI extremely widely, as shown by the following data presented at the World Economic Forum by representatives of the consulting firm BCG:

The ability of artificial intelligence to continuously learn and adapt to dynamically changing conditions makes AI, in the long run, have the potential to reduce market volatility by introducing a kind of data-driven discipline.

However, one mustn't get carried away with the power of AI - remember that AI systems still raise ethical concerns first, and secondly, are not yet well described regulatorily. So it is important to make a careful consideration and find a balance between using AI everywhere we can and responsible trading practice.

A Bit of History: Market Data and Stock Prices

Let's go back for a moment to January 1999 - MIS International was then in an extremely difficult situation. They had no profits, and the stock was trading at just $0.50 per share.

However, they knew something that wasn't so obvious to the rest of us at the time - they realized perfectly that the phrase "dot com" would revolutionize the market and provide companies with profits.

So they changed the name to Cosmoz.com. And guess what? Just because of this move, their stock went up by... nearly 1,000% to $5 a share.

Exactly the same phenomenon happens today. Artificial Intelligence. AI now has a hype take like "dotcoms", but there are still cases where it works and is useful - not like just changing the name to *.com. So let's take a look at the opportunities this technology offers for the investors in the financial markets.

Much More Than a Standard Data Analysis

Artificial intelligence algorithms can process huge volumes of data, providing investors with highly accurate conclusions. Let's face it - when relying on traditional methods of analyzing stocks and markets, people involved in investing in the stock market will not be able to physically cope on their own with such an amount of information and with their imperfect interpretation, which, as a consequence, may turn out to be a simple way to overlook emerging financial opportunities or wrong judgments of the overall market situation.

In literally less than a second, machine learning algorithms can make clear guidelines for investors worried about proper market decisions.

1. Feature Engineering

This is the stage of work at which, from the collected and processed data, features are extracted that represent the decayed aspects of the financial market, including other indicators, like moving averages, news sentiment scores, volatility or, for example, trading volume.

2. Model Development

AI is outstanding at creating predictive models responsible for exponential growth - suffice it to mention example methods for teaching the model, like decision trees or so-called random forests. All this, in the long term, helps in the decision-making process. Moreover, AI programmers can divide historical market data into two categories: a training set and a testing set. The training set is used for training the model, and testing is, as the name suggests, for testing on "unknown" data to see if the model performs well. In the former, the algorithms learn to recognize patterns and correlations occurring between features and stock price movements - so that, having already gained this knowledge, they can transfer it to the test model.

It is interesting to note that teaching the largest models can take a few or dozens of hours - or even days.

3. Trading Signal Generation

Once the model has been designed and tested, it's time to implement it for real in daily work and start generating trading signals (based on the analysis of real-time data that was not part of the training or test datasets). Thanks to this, you will be able to decide whether to sell, buy or leave the selected stock.

4. Risk Management

Artificial intelligence can become experts in risk in controlling and determining the level of exposure to potential losses. AI-based systems perfectly handle stop-loss levels, based on current market conditions. This is because the AI system algorithms are able to identify quite unusual trading patterns that can indicate potential market manipulations. This allows them to recognize fraudulent activities in advance - with greater speed and efficiency than humans.

Summing Up: the World AI Revolution

AI is one of the biggest technological advancements of recent years present in almost every industry. It makes our daily lives much easier and allows us not only to benefit from autonomous vehicles and other eye-catching solutions but also - to invest wisely. AI algorithms are free of human intuition or related behavioral biases. What's more, AI continues to evolve rapidly, working on brand new developments and solving really complex issues, taking into consideration massive amounts of various factors.

AI algorithms increase efficiency, acting like your personal assistants, helping you avoid market manipulation and improving decision-making process.

The future of stock investment is about processing information and avoiding potential risks. After all, only basing on more informed decisions can lead to adjusting proper strategy. It's something more than just a current trend - this technology is a song of the future for many investors. Smartly used, well-designed AI-model can lead you to your private Wall Street. Try AI-powered technology out - and find your own set of stocks and best-case scenario for financial future.

"AI = Increased Efficiency" Statement: Truth or...Risk?

However, we encourage that decisions to use AI be fully thought out. AI and roboadvisors are a new, exciting take on passive investing, which promises not only saving time but often also profits way above the average. While innovative and exciting, AI still faces a lot of challenges on the way to broad adoption — many people are hesitant to put their savings into the hands of a black-box algorithm promised to be working, but its full and guaranteed correctness is impossible to verify, even for engineers who implemented them. It’s like with self-driving cars — even if it works perfectly 99.99% of the time, none of us wants to be this unlucky 0.01% for which something went wrong, as the consequences can be absolutely horrible.

The trend we observe is the growing popularity of tools like Scrab.com, which automate the repetitive aspects of research and speed up the investing process allowing for more informed choices free of false information, but are 100% transparent, and their output can be verified - giving people something more reliable and trustworthy than an AI-powered “just believe me, it works”.

PS. Besides, remember that AI is not infallible, and the funniest example of this is... dogs and cookies, the famous "experiment" based on the question "Chihuahua or muffin?".

It turns out (for your entertainment and education) that the generative AI has trouble distinguishing cookies from dogs. Of course, it is difficult to transfer image recognition directly to the stock market, and artificial intelligence, contrary to appearances, learns from its own mistakes (and the more muffins and new data it "sees", the better it will be able to distinguish them) - but sometimes it is better to still trust your decisions at the end of the day, and not blindly follow the AI expert systems :)