What is the future of capital markets, including (sports betting)?

 

We live in an age where technological advancement is faster than ever before. This is true of all areas of our life. Technology is one of the main components that influence the economic development of entire societies. Today we will consider the impact of technology on ordinary capital markets, including sports. We will try to answer to ourselves what consequences it can have, including the current stage.

 

Who makes money on the markets?

 

The vast majority of individual investors who are part of the capital markets lose. It is estimated that it is over 80% of the players who participate and create the market. It is logical that if someone earns, then someone else must lose. Speculation plays an important role in numerous assets, which is the subject of many emotions and hopes. In sports markets, speculation is also of lesser importance because we can speculate on the odds changes themselves, a few hours or days before the game, but the rules are quite different.

The question of who actually earns can be answered by viewing the many results of individual investors. They function mainly in the capital markets, but they are also in the sports markets! Which many people don't know. Individual investors do not make decisions based on their own subjective beliefs or the mood that accompanies them on a given day, which cannot be said about the other group.

Also, many of them already use learning machine models that de facto make decisions for them. As we all know, data is the new synonym of wealth today, and it is from this data that institutional investors draw on an unprecedented scale. Big data processing has become a multi-billion dollar industry that is constantly growing. The impact on the capital and sports markets is just one of the many elements that make up this industry.

 

The hinto product and Big Data

 

The concept of Big Data has been with us in the mainstream media for some time. The average person, hearing this term, is often not fully aware of what it entails. The number of uses is powerful. In fact, wherever we generate data, big data can be used for specific business needs and more. But let's try to present the use of big data on the example of the Hinto product.

Our product could not function without the data we use to present every single prediction that appears on the platform. Everything you see on our platform is mathematically justified by processing large data sets. Thanks to this, our solution allows individual users who have access to a tool that allows them to make responsible and strategically consistent decisions. We decided that we did not want to close our solution to the institutional path, as every major player does. We believe that our non-standard approach will satisfy a certain market area that no one previously paid attention to.

This is a response to the accusations that are often made. If your algorithm works, why are you making it publicly available? To a certain extent, the answer is straightforward: we can be more business efficient using the algorithm instead of closing ourselves to using it only for our own purposes. We want to point out that we also use it ourselves, but we don't see any contraindications to share it with others.

 

What could be the future consequences of using algorithms in sports and capital markets? 

 

This question is fundamental. As we also emphasized in the previous answer, our product will work very effectively up to a certain scale, making it necessary to restrict access to it. For a long time, we will not be in danger because we also have many solutions planned that we can implement in such circumstances, increasing our upper barrier. However, when analyzing a macroeconomic scale, one should be aware that technological solutions will stop working in terms of making decisions based on data because everyone will start to use them in the case of capital markets. As long as players rely on their own knowledge, intuitiveness, and strategy, these parameters will always be more unreliable, from solutions that generate proposals to make specific decisions based on data.