Index Trading With AI: Betting On The Future

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

One of the obvious advantages of being a stock market titan like JPMorgan Chase or Goldman Sachs is the volume you are working with. When longing or shorting on millions of stocks, the returns are set to be truly gargantuan – and so are the losses, potentially, unless you are smart with your risk management. But what if you, as a retail investor or trader, do not have an appetite for individual stocks? What if you also want to trade baskets of assets, not just a few tools? Index trading is the solution you seek – or, better yet, AI-driven index trading, just to keep up with the world.

But let us not get ahead of ourselves. What are stock market indices, how does one trade them, and why bother at all? Keep reading to find out.

Market Indices And Index Trading

A market index is a benchmark for measuring the performance of a specific equity market, or even a sector, like high-tech or AI. The index is normally calculated based on the price action of the top stocks comprising this specific investment universe, as a weighted average, for example. Thus, the index reflects the overall state of the equity market that it represents, working as a convenient tool for traders and investors alike in their strategizing.

Price action candle chart
(Source: Pixabay.com)

Now, since what we are talking about is essentially a benchmark rather than an actual portfolio, the first thing to note is that you cannot really trade indices per se. What you can trade, is a whole variety of derivatives that are based on the most popular indices, be it S&P 500 or NASDAQ.

Options and futures contracts are among the most popular derivatives for index trading. Index futures are legally-binding cash-settled agreements that are essentially a bet on the future movement of a specific index. Index options are less binding in the sense that they give you the right to buy or sell the underlying rather than force you to do so, as futures do. As for the underlying, what we are talking about are the aforementioned index futures. These financial instruments are favored by those looking to hedge their portfolio against the changing tides of the market and speculative traders alike.

As an alternative, you could opt for CFDs, or contacts on difference, a derivative that is more accessible for retail traders. The idea behind it is pretty much the same as with the index futures, in the sense that you are betting on the future movements of the index. The difference, however, is that a CFD is an agreement between the trader and the broker. Thus, if you are considering these derivatives, make sure to do proper research on the broker and look out for scammers.

Finally, another security that closely mirrors the index movements are ETFs, or exchange-traded funds. These are funds holding a large portfolio of stocks that make up a specific index, and thus, the price action of their securities follows that of the underlying index. ETFs are a solid choice for those looking to buy a share in a specific market or investment universe rather than deal with the risks connected with individual stocks.

AI-Driven Tools For Traders And Investors

Now that we are familiar with what indexes stand for, it is time to quickly go over another piece of our puzzle – one that just so happens to be capable of bringing both retail traders and institutional huge profits by working as a high-tech crystal ball for telling the future of the markets. But while fortune-telling is not considered a precise or empirical science (or a science at all), that is not the case for statistics. And, in fact, it is advanced statistics that lies at the core of machine learning, a major hot topic for today’s financial world.

Lines of code on laptop screen.
(Source: Pexels.com)

Machine learning is all about having the computer process a dataset and come up with a mathematical model that describes the patterns found in the data. This formula, which can be either quite simple or super-complex, based on the algorithm that we are using, is then utilized to work on one of the two fundamental tasks. These are prediction, in other words, trying to predict a certain unknown value based on the known values, and classification, which is about ascribing an object to a certain category based on its known features.

Machine learning can be split into supervised and unsupervised learning (with semi-supervised learning essentially being a hybrid). In supervised learning, the programmers explicitly tell the machine what kind of formula they expect it to deliver, and what variables need to be accounted for in it. With unsupervised learning, however, the machine is to figure this out pretty much by itself.

If we take into account the fact that all this normally has to do with processing huge troves of data and meticulously crunching the numbers to deliver the result, it becomes clear why the AI tech is such a boon to the financial sector. The use of AI is blossoming in this world, with machine learning algorithms taking on a whole variety of functions. And investment strategizing is one of the areas where AI shines.

AI-Driven Index Trading With I Know First Algorithm

Since we mentioned prediction, one of the things that people are, understandably, most happy to try and predict are stock markets. One of the leaders in AI-driven stock market prediction is I Know First, an Israel-based company that has trained a deep learning AI, which delivers daily predictions for over 10,500 financial instruments, including ETFs, stocks, and indices.

Now, as we note earlier, a major deal of the derivatives that index traders work with are essentially bets on the direction that the underlying index is going to take. Thus, it is quite easy to see why AI-driven index trading holds this much of a promise. Traders want to know where the indices will be on the maturity date, and AI offers a way to cross-reference your own analysis with the findings of a complex algorithm.

So how does all this work?

Inforgraphic: how the AI algorithm works
(Source: Iknowfirst.com)

The I Know First AI is based on deep learning, which is one of the hottest types of machine learning. It relies on deep neural networks, which mimic the way the human way works by running the input through layers of nodes. This means that the input goes through a variety of mathematical transformations before the output is delivered. This high degree of complexity allows deep neural networks to handle tasks that are beyond the realm of possibilities for a simpler algorithm.

Trained on a historic dataset covering 15 years of trading, the I Know First AI studies the markets from a holistic point of view, looking for trade signals in fresh market data. It delivers its forecasts as heatmaps with two numeric indicators: signal and predictability. Signal shows the relative difference between the current price of the asset and the price that the AI sees as fair for it of the asset. A strong positive signal means the asset is about to go up, and a strong negative one warns of an upcoming plunge. Predictability is an indication of how accurately the algorithm has been predicting the asset in its previous forecasts. It ranges from -1 to 1 and is defined as the Pearson correlation rate between earlier forecasts and actual price movements.

The algorithm incorporates elements of genetic programming in its design and keeps an eye on its own performance. It updates its predictive models as soon as they stop to reflect the current market conditions. This makes sure its predictions maintain commercial relevance under any market conditions and ups the accuracy of its predictions with every new forecast.

The 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, which helps traders pick the stocks to long and short.