This article was written by the I Know First Research Team.

Your trading strategy needs a moat. No, seriously, ask Warren Buffet – he is a huge fan of moats, moats is what he looks for in the companies he invests in. Not real moats, of course, those would look more appropriate around a medieval castle, not the new Microsoft office, but moats that help the business stay ahead of the competition. Similarly, your trading strategy needs something that will help it stay ahead of the markets – and that something could be a stock market prediction AI.

But hey, you may say, hold your horses – what’s that moat thing, why do I need it, and what does AI have to do with all this? Well, all of those are very good questions, so without further ado, let us dig into this.

How Moats Make You Money

So what is an economic moat? A term popularized by Warren Buffet and picked up and brought to new fame by Pat Dorsey, founder of Morningstar, an economic moat is something that helps a company secure competitive advantage over the competition. Competitive advantage, in its turn, is the ability to push out similar products while generating more profits than your rivals.

While these two terms could potentially be seen as quite similar, the difference is that a competitive advantage can be chipped away by the competition as it adapts to the disruption that you just caused, while a moat is not as easy to walk over.

As an example, let us imagine that we are opening a business – a small company carving various home decorations of stone. And, lo and behold, we will be able to sell our product at a price that is 20% lower than that of our competitors, because we found a supplier who is ready to sell us large batches of raw materials at a 20% discount. What happens next? Shorty, the rest of the carvers in the area would also turn to the same supplier, which would erode our lead.

Now, consider a different scenario: we came up with a high-tech carving device that allows us to minimize the waste of material in production. In other words, we are able to carve 10 statuettes out of the amount of raw material our rivals use to carve 9. We patent the device, making sure our competitors cannot use it, and reap the long-term benefits of a competitive advantage secured by a moat.

There can be other moats as well, not just patents. For example, if our carving company were to switch a different supplier, we could run into some extra expenses – such as having to re-gear our wonder-cutter for the new raw material or re-building the logistical network. These costs are a moat for our current supplier. Other things, such as a strong brand identity and a loyal customer base, are also economics moats. As we can see, moats can often be quite difficult to quantify, but they are bulwarks against failure.

So far so good, but again, what about trading, and what does AI have to do with all of this?

Conquering Alpha With Stock Market Prediction AI

As we established, an economic moat is your bulwark against losing the competitive advantage. In stock market trading, however, things are much less about beating another trader. Here, you have to beat the market itself – or, in other words, make the money on its movements, whether it is going up, sliding down or bouncing back and forth in a fit of volatility. To do so, you have to, effectively, predict the future state of the market from the data at hand. There are many ways to do so – you can look at the fundamentals to pick the stocks that look underpriced, you can place you bet on a specific sector or rotate your money across different sectors to make sure you only bet on the winners. Means are different, but the goal is the same – trying to navigate your way around the market uncertainty via rigorous analysis.

And this is why an AI capable of delivering accurate stock market predictions could work as a moat to your success. By using its predictions in your strategy, you make sure that there is no human bias involved. Also, you get a chance to double-check your calculations against the AI’s forecasts, thus decreasing your risks and being able to only bet on the safest options.

Such predictive algorithms already exist, and to use one, you do not have to be a large institutional player, like JPMorgan Chase. Tech-savvy startups are there for you, seeking to level the playing field and make AI-driven trading accessible to everyone. Among these is I Know First, an Israeli company that has designed its own stock market predictions AI.

The deep learning-based algorithm delivers forecasts for over 10,500 financial instruments, including stocks, indices, and ETFs, on a daily basis. Trained on a dataset covering 15 years of trading, it approaches financial markets from a holistic perspective, processing fresh trading data to model the trends and pick out the best stocks to long and short.

The algorithm delivers its forecasts as an easy to interpret heatmap with two numeric indicators: signal and predictability. Signal works as a relative measure for the estimated difference between the current price of the asset and the price that the algorithm assesses to be fair. A strong positive signal means the asset is expected to rocket, while a strong negative one is a promise of a nosedive. Predictability shows how well the algorithm has been predicting this asset before. It ranges from -1 to 1 and is calculated as the Pearson correlation rate between earlier forecasts and actual price movements.

The stock market prediction algorithm can adapt to new market conditions on the go, because it incorporates elements of genetic programming. Aware of its own successes and failures, it updates its predictive models whenever they seem to be losing their ability to adequately predict the market. Accordingly, its accuracy goes up after each learning cycle.

The stock market prediction AI also draws on chaos theory to account for market volatility. It delivers its forecasts for time horizons ranging from 3 to 365 days, covering short, medium and long-term perspectives. In a string of recent evaluations like this one, it demonstrated an accuracy of around 60% for 3-day predictions, rising up to 80-90% for 3-month forecasts, which is more than enough to generate consistent profits on trading.