Technology is evolving exponentially in the modern world, and we are continuously seeing applications of AI tech that would have been considered science fiction only a few years ago. 

But can AI really replace human-generated trading decisions? 

We’re going to explain some major similarities, differences, pros, and cons to help you decide for yourself. 

What Are AI Trade Signals?

Artificial intelligence (AI) trade signals are signals that are being generated from a computer’s interpretation and analysis of large sets of data. The signals AI provides are essentially the product, or output, from a machine’s interpretation of large sets of aggregate data. 

AI signals are becoming more and more prevalent in our modern world as computers continue to advance. In fact, according to a recent SEC report, 70-80% of the trades placed in equity markets were placed by computer algorithms and not humans. 

The newest generation of computers that place the trades use machine learning and do not have a predetermined, rigid way of being programmed. With a more flexible way of attaining goals, everything that occurs with a security while the computer is learning (like volatility/ price movements), is used as data for the computer to make better decisions for the future.

This is similar to how we learn. If you stick your hand in a fire, next time you’re around a fire you will know to be more careful and keep your hand away from it. While a simplistic example, the same principle applies.

A computer can take in extremely large sets of data to produce trade signals. Some of this data includes things like historical pricing and volumes, chart patterns, and volatility. 

How Do AI Trade Signals Differ from Human Signals?

The short answer is obvious, one signal comes from a computer and the other from a human. But we want to dive a little deeper here to give you more than the obvious answer. We’ll explain some similarities and differences, as well as highlight some of the key pros and cons for each type of signal. 

Let’s start with jumping into the first major difference.

A Powerful Guide: The Heart

The first major difference between humans and computers is that humans have a heart. Here, we are talking more about intuition and emotions, and not necessarily the physical heart. The heart can feel, it can know. Then the mind can interpret and make decisions based on the intuitive input from the heart. The complexity of the emotions human experience is not something that exists in computers. But can emotions be beneficial when used to trade securities, or are they detrimental to our decisions? 

Emotions play a major role in our decision making, as well as our interpretation and feeling towards different situations and processes. Imbuing emotions into an investment decision can be dangerous when it comes to the stock market, but they can also be advantageous when used correctly. 

Fear and greed are dangerous emotions in the market because they can cloud your judgment and lead to you making decisions that aren’t rational, such as doubling down on a position because you greedily think it will keep going up. When things don’t go as planned, you’re stuck watching the position’s value decrease and lose double the amount of money you would have if you remained more rational. Humans need to remain mindful when they trade in the market so that they are aware of these emotions. 

AI does not have to worry about this, as our expression of emotions and intuition is not something computers possess. Humans need to take extra care to make sure they act from a rational place. 

The advantage to emotions, however, and what might give humans an advantage over AI, is that emotions can allow you to have a finger on the pulse of something computers can’t feel. That is, humans have the ability to empathize with others, allowing them to gauge market sentiment on a level that’s categorically unavailable to AI (at least for now). 

How do emotions affect trade signals? Making emotionally based decisions is a lot more common with new traders than it is with seasoned vets. Expert traders are aware of the dangers of emotions when they influence investment decisions, so they mindfully act from a more rational place. And since good signals are provided by these highly experienced, veteran traders, a machine probably doesn’t have a significant edge in this regard. 

The signals TTA provides are all generated through highly experienced humans, not machines. We believe this gives us an edge, even when compared to computers. In our case, we let our strategy – and its results – speak for themselves. 

So a rational, seasoned trader that can use emotions to their advantage, and then make sensible decisions based on logic might actually make AI signals an inferior option to human signals.

Here, we’ve discussed a huge difference between humans and machines. So, what’s a similarity between the two? Let’s get into that now. 

Intuition and Data Driven Decisions

Intuition, or an intuitive feeling, can be thought of as a feeling or idea that manifests from a series of patterns and inputs. Something we often call a “gut feeling.” We’ve all had those “ah-ha!” moments – this is the intuitive spark. It is then up to our mind what we do with these feelings and insights. 

Here’s an example of gaining intuitive insight: you’ve been working on solving a problem for some time, say it’s a move that you want to make in the market. You’ve been reading research reports, conducting technical and fundamental analysis, and you feel that you’re getting close to figuring out a strong buy opportunity. Then, seemingly out of nowhere, you suddenly have a realization that a great idea would be to buy TSLA and hold it until the end of the week. 

It’s as if all of the information that you gathered aligned itself into a single decision, into an “ah-ha!” moment. This is something that computers do also. They make data driven decisions. And the more data they have, the stronger a decision is (from a statistical point of view). 

We can liken this to our own experience as humans. When we have various experiences and inputs like looking at a company’s financials, experiencing a market recorrection, etc., we are gathering data that can help us make better investment decisions in the future. 

The tricky part, and where the difference lies between humans and computers is what we do with intuitive insight, and how reliable and consistent those insights are. One problem is that an intuitive insight isn’t something that comes to be through a conscious thought process—so it really cannot become a backbone of any trading methodology. 

Plus, even when you have those insights, humans have a tendency to overthink things, so something that seems clear can quickly become convoluted. Like when you’re taking a multiple choice test and you immediately think the answer is “A”, but then you overthink it and get the wrong answer by choosing another option.

Moreover, we can’t just assume intuition is always right, as a human’s tendency to think into something that is felt can lead us to making incorrect assumptions. So even if you get some intuitive trades right and others wrong, it is still a really vague variable in a human signal provider’s performance. Since robots don’t suffer from intuition, they tend to make more consistent, reliable results (at least in theory). 

This sounds like intuition may be a disadvantage to human signals, but if anything, and if used correctly, it could just be something that helps. It’s up to a person to determine what we do with those insights, and those insights can be taken with a grain of salt and simply used as another perspective and or input. Computers are limited to just making data driven decisions, and then it stops there. 

Computers: Inputs to decisions. 

Humans: Inputs, to potential insights (which can be thought of as more inputs), to decisions. 

The seasoned vets that create trade signals know how to use intuition that they’ve gained from sometimes decades of experience into a single decision; and they’re not limited to being forced to make a data driven decision.

What the AI Cannot See

AI is limited to only the data that it is programmed to collect. So while AI might be able to analyze massive sets of data, there are some huge gaps in potential inputs it could have. 

We all remember what happened with GME. We saw just how much influence a Reddit community actually had, something that was vastly overlooked. Reddit community, WallStreetBets page on Reddit that has a following of over 11m members as of December 2021. This group has been viewed often as a herd of profligate, young investors (or rather, apes who watch stonks that only go up). But in January & February of 2021, we saw just how much influence they had on the market. Causing some titan sized investment firms to lose billions.

This really threw AI’s algorithms through a loop. It’s not uncommon for hedge funds to rely on AI tech to drive their decisions, and what happened with GME is something that would be impossible (currently) for an AI to have detected. As humans, however, we could have seen this coming and used it to our advantage versus watching it annihilating our capital.

Without enough data to work with, AI traders overwhelmingly failed to make the best out of the GME saga, unlike many retail traders. Image by TradingView.

So in theory, a major weak point of AI engines’ are events that had never happened before. Signal providers that have human generated signals have the ability to examine data that a computer might not be able to. 

Cost vs. Benefits 

The last element that we want to discuss here is the cost and benefit you gain from having either AI generated signals or trading signals from a human. In theory, once you make the AI, it doesn’t need a pay check, so you might assume that those services are less expensive; but in order to teach it, the AI needs a LOT of processing power. So, as it turns out, evolving an AI entity isn’t cheap. 

You can expect to pay hundreds if not thousands of dollars per year on market-leading AI signal providers. And while prices (both annually and monthly) vary greatly provider to provider, it is not clear that AI providers are consistently less expensive. This means that the next element to look for in a good provider is their return.

It’s important to look at a provider’s return-on-investment (ROI) because while prices may be low, their ROI could likewise be low. You want to know if your costs are matching, or, favorably, are less than the benefits you want to receive.’ With returns, there is not a huge difference between the ROIs of human and AI generated trade signals. So it’s important to compare the cost of the service with the ROI they market to make sure you’re getting your money’s worth.

In turn, both humans and AI generated signals can generate successful trades. What’s more important is the particular service you opt for, its track record, and its reputation. The leading signal providers will explain why they’re the best – in a transparent manner.

The Future of AI in Trading

Considering AI’s progression from its initial use to its applications today, it is clear that it will only get smarter and its applications will only get wider as we move into the future. 

The potential uses of machines in their application to topics related to finance has been talked about for well over 50 years. We started to see just how useful machines could be to helping with topics related to finance in the 1980s. During this same time, two thirds of all Fortune 500 companies used these types of systems on a daily basis. Using knowledge based systems, or expert systems, companies could use machines to help audit and make predictions in the market. 

Protrader was one example of this. This was a system developed by K.C. Chen from the School of Business at California State University & Ting-peng Lian of the University of Illinois. It was able to predict the 87 point drop of the Dow Jones in 1986. That was 35 years ago… 

As time goes on, AI will likely become more and more competent. More intelligent. It is hard to say where it will be in 5, 10 years. But we have already seen an incredibly fast progression in technology and specifically AI. Considering where the technology was a few years ago to where it is today, we can only imagine where it will be in the future. 

Will they eventually become the optimal option for those deciding between a human or an AI signal provider? Or will humans always have an edge against machines that’s hidden in our biology, our makeup? Humans are curious, they can discuss, crowd source information, intuitively feel, experience complex emotions, etcetera. Maybe these characteristics are irreplaceable, or maybe they aren’t… 

The future is both an exciting, and scary place when considering how AI will progress. Again, it’s hard to say exactly where it will go. But what we can say for sure is that at TTA, we’re going to continue doing what we know works. That’s employing an effective risk management strategy, keeping the strategy strong yet flexible, and sending consistent, human generated signals in the market based on years of experience and careful analysis. 

Human Traders vs. AI-Generated Signals: FAQs

How Helpful is AI as it Applies to Trading?

We believe computer based technology to be helpful as it applies to trading, clearly. But it cannot be relied on entirely. 

How far AI has come in it’s application to the finance world is similar to where self driving cars are. They can drive on their own. But very few, if any, would trust them 100% to drive them somewhere while blindfolded. The technology is incredible, and it’s potential uses are exciting, but it’s just not at a point where it can be successful without human intervention. 

So AI for trading should be thought of as a helpful tool. It’s not the tool that builds a house, (or a strong portfolio) it’s the builder, or investor that’s using the tool to make what they want. AI should be thought of as more of a helping hand than a mentor, for now. 

How is AI Trading Different from Algorithmic Trading?

In essence, the main difference between AI and algorithmic trading (sometimes referred to as algo-trading) is how the human interacts with them. 

Algo-trading requires more human interaction than AI does. This is because there are conditions, or rules set by humans (like price, time, intersections of moving average lines, etc.). The computer will operate within it’s given parameters, and save the human user tons of time because the computer is constantly monitoring the market. This is similar to setting a stop loss, just more complex in the case of algo-trading. 

AI is more ‘human-like’, if you will; it acts more freely than algorithmic trading, changing dynamically as it learns from varying conditions in the market. With each new input to the AI trading software, it learns, and never forgets that information, continuously evolving and becoming more effective (statistically) in predicting the future. 

Perhaps a comparative metaphor can be: algo-trading is kind of like a calculator, you put in the inputs manually, and then the computer does the rest of the work. AI is more like a human—thinking, in a sense, and continuously evolving, learning.

How Popular is AI Trading Software?

The popularity of AI trading software is definitely on the rise. It’s recognized by many as cutting edge tech, and is used often by companies in the finance industry. But while the companies are accepting of it’s application and understand it’s potential, since it is still relatively new, they aren’t all readily making the switch to AI. 

Considering the development in AI, it’s popularity as a contemporary topic in the media is through the roof. No one is unaware of its existence. However, its popularity in employment by people and business as a tool is a lot less. As we have touched on above, while AI is impressive, and it’s potential applications are incredibly vast (can even be scary to think about at times), it still has a long way to go. 

Bottom line is, while the results in the effectiveness and usage of AI seem to be a little skewed, we know that some companies are really going for it, relying entirely on AI to build their models and strategies. And of course there are some who stick to the old fashion way, and seem to keep computer use at a minimum. 

Will the Acceptance of AI Tech Bode Well for the Future of the Stock Market? 

There is a good quote from the movie Jurassic Park: “Your scientists were so preoccupied with whether they could, they didn’t stop to think if they should.” Should we be asking ourselves “can we” implement AI?, or is the real question “should we?” We believe that the potential for AI is strong, and could bode really well for the future of the market, but we need to tread lightly. 

Should AI be used to assist humans making the ultimate decision, or perhaps would it be better for AI to make the trades exclusively? These are tough questions that don’t currently have definitive answers, so only time will tell. What we do know is that they can be a fantastic tool, and there isn’t clear data or information that suggests AI can outperform a human investor. 

Through this, we believe that accepting AI as a tool used by humans versus substituting a human is the best approach for a sustainable technology future. It’s important to remember just how complex human biology is, consciousness, our ability to empathize and experience emotions on the level we do, are all extremely beneficial aspects that humans have, and when used correctly, can make very effective  decisions. These tools are unavailable to AI. 

So while the future can be exciting when thinking about AI’s involvement with it, let’s again, tread with caution, and think sustainably.