Investment Strategies and AI: New Tools For Time-Proven Practices

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

Choosing the right investment strategy is a very important step towards reaching your financial goal, whether it is accumulating enough to buy a cottage house or living the life of a millionaire after retirement. The way you build and manage your portfolio largely depends on your appetite for risks and the available funds, as well as your personal preferences and understanding of the market. Thus, it is no surprise that there are quite a few investment strategies out there, and while quite many of them have been showing good results, there is still room for improvement. The booming artificial intelligence technology has been a boon for the financial industry, and in this article, we will show why some of the most popular investment strategies and AI are a match made in heaven.

Artificial Intelligence: A Booming Industry

The artificial intelligence has turned into a buzzword these days, to the point where it can at times be difficult to figure out what exactly this umbrella term means. In this article, AI will be used interchangeably with machine learning. The latter sees the computer process a dataset and come up with a mathematical model that would be based on the patterns that it has been able to pick up. In other words, what we are talking about is advanced statistical programming rather than an actual intelligent and self-aware consciousness.

AI and Investment Strategies

To be fair, we need to say that machine learning as such is an umbrella term as well. Fundamentally, we can split it into supervised and non-supervised learning (there is also semi-supervised learning, of course, but let us keep things neat and understandable). In supervised learning, we explicitly tell the machine what are the variables we want it to work with, and what type of relationship exists between these variables. With unsupervised learning, however, the computer is expected to figure things out all by itself. An important thing to note is that data does not have to be structured, or presented in a way that would make it easily readable to the machine.

Now, while there are different machine learning algorithms, neural networks are perhaps the best-known one, at least if you look at the headlines in the media. Neural networks approximate the way our brain works; these are complex, layered mathematical functions that run a bunch of transformations on a given input to give the output that they have been trained to deliver. As an example, if you train a deep neural network to identify cats in images, the first few layers may identify the edges in the image, the next one will look for shapes, and it will proceed this way until the cat has been found or the AI is sure that there are no cats in the picture.

If you take into account that AI algorithms are generally good with processing huge troves of data, especially numeric data, and classifying or predicting things that this data describes, it is no wonder the technology has been a boon for finance and fintech. And investment strategizing is one of the areas where AI shines.

Most Popular Investment Strategies – Overview

As we noted in the introduction, there is a wide variety of approaches and strategies out there just due to the fact that you can do investment in so many ways. However, it is still possible to highlight the strategies that have accumulated more of a following over the years, those that are best-know in the investment circles. And the first one to note among them is, of course, value investing, popularized by none other than the legendary Warren Buffett himself.


While the strategy is discussed in more depth here, but the gist of it is that you essentially follow the logic of someone looking for a deal at a Walmart sale. You find the stocks that are undervalued by the market, throw them in your basket, check out and wait for everyone else to realize that they also want what you have. At this point, the stock price starts to live up to the company’s actual value, boosted by the market’s demand, and this is where your profit comes from. This approach to investment can often include longing stocks and committing to your investment in the long-term. Quoting Buffett, the Value Investor Extraordinaire himself, “if you aren’t willing to own a stock for 10 years, don’t even think about owning it for 10 minutes”. Value investors can utilize tools like contrarian investment (investing in the underdogs) and rely on fundamental analysis to assess the value of the company.

Another approach, known as sector rotation and reviewed in more detail in this article, is focused on picking the best-performing sectors and investing in the best-performing companies within these sectors. Then, as some sectors and companies lose steam and others get ahead, you re-balance your portfolio to make sure you are still betting on the winners. Since these transactions normally come with a lot of extra expenses like fees, you do need a large asset pool for this strategy to work as you will be able to offset those. Thus, this strategy is better for large institutional investors rather than private ones. At its heart is an investment philosophy known as momentum investing, where the idea is to invest in the winners and short the stocks that are going down relying mostly on technical analysis. 

Alternatively, you could go for the so-called growth investing and instead look at the companies that show the best growth. Here, you may look for smaller companies with higher potential, studying their consecutive profits and revenues and looking for the ones that seem to be rocketing, or opt for giants like Facebook that demonstrate stable growth. The proponents of this strategy can find themselves investing in a stock that is not necessarily too optimal in terms of price-to-earnings ratio. This is not what matters here, however, because this is all about the growth. Oh, and don’t expect too much in terms of dividends, since most of the money the company makes would probably go into more growth.

Or, if the risky nature of growth investment does not look too appealing, you could also look for assets that bring in the highest and steadiest returns. While this is not necessarily as lucrative as investing in stocks, longer-term Treasuries or ETFs can be a source of a steady and reliable income. They can be a solid choice for those with a low risk appetite or those in possession of funds large enough to make such investments pay off handsomely.

Finally, if you feel that you have a special understanding of a specific industrial sector (or would not mind developing it, or just feel that its future is the brightest one), you can focus on it and throw your eggs into more or less the same basket. Here, you can invest in the appropriate ETF or, alternatively, take a bottom-up approach and invest in the stocks of specific companies within the sector. This top-down versus bottom-up can also be found in the sector-rotation strategy.

Investment Strategies and AI: Here Comes The Future

Now, AI is already widely used in the fintech industry, and everyone working with investment, including banks and private funds, has been taking notes. As a result, artificial intelligence has already been introduced to the world of investment, and while many algorithms are implemented by large institutional investors behind closed doors, there are also companies that seek to make algo-trading more available to the general public. Among them is an Israeli company called I Know First, which has trained an advanced deep learning AI to provide investment advice to its customers.


The AI has been trained on a dataset covering 15 years of trading. It also draws on the chaos theory to account for the chaotic nature of the stock market, and incorporates elements of genetic coding, which allows it to increase the accuracy of its predictions with every iteration. The algorithm goes through fresh trading data and models the price dynamics for over 10,500 financial instruments, including stocks, ETFs, commodities and currencies. Its predictions are delivered as an easy to interpret heatmap with two numerical indicators: signal and predictability. Signal indicates how a given asset is expected to perform relative to the other assets on the forecast, and predictability shows how well the algorithm has been predicting the price fluctuations for the asset up until this point. The predictions cover a wide range of time horizons, from 3 to 365 days.

These forecasts can work as a useful tool for proponents of a wide variety of strategies. Data-driven insights on the company’s expected future performance can be a boon for proponents of a value investing, for example – long-term forecasts rather than short-term ones, that is. This prediction will work as yet another tool for them to see how much value the company can generate in the long run, and whether this would be enough to make it a worthy investment.

Momentum investors would be even better off using this tool, since it basically works as a way to outsource technical analysis. Technical analysis looks for trends in the trading data, and so does the I Know First AI algorithm – at a scale large enough to encompass thousands of assets and dozens of sectors. Thus, its predictions can be used either for picking the stocks for long and term position or as a way to cross-validate your own analysis with the help of an advanced algorithm. Numerical output means that the forecasts will be easy to use as weights for figuring out the ratio for investments across different sectors, not to mention the fact that they can easily be used to pick out the best sectors in the first place.

Income investors would benefit a lot from the predictions on interest rates, which would help them maximize their returns without losing any of the benefits of their selected investment method. Sector investors would also benefit from the ability to do bottoms-up analysis of their selected sector using forecasts for individual companies – or get a forecast for the ETFs of their choice, if that is what they prefer.

Finally, since a good portfolio needs diversification and risk hedging regardless of the grand strategy behind it, all of the above will benefit from the opportunity to look into assets to invest in as a hedge against the tides of the markets. Commodities like gold are traditionally used for that, and the I Know First AI does deliver forecasts for gold prices, as well as other assets reserved for limited just-in-case-investment.

As we can see, AI-driven decision-making enhancement tools fit nicely with a lot of the conventional investment strategies, which, on a more philosophical note, makes us think that the future of fintech is in broader adoption of AI assistants rather than AI replacing humans as traders and asset managers. The human mind and AI have their respective strengths and weaknesses, and the interplay between them promises too much an opportunity to give up on.