Unlocking the Potential of Data-driven Investing
Once in a while, something happens to a business that changes the game completely. Be it an invention of the conveyer, artificial intelligence, or the internet – once it occurs, things cannot go back to the way it was before. The latest of such crucial turning points in business was informational. Data is now the driving force behind many procedures related to business and finance. The purpose of this article is to look at one such method, namely, data-driven investing. The potential of this new approach to investing makes it something that the investors of the future cannot afford to miss.
Choosing the right approach
At first glance, the idea of investing might seem quite simple to an outsider. One puts their money in stocks, companies, projects, etc., with an expectation to get more money back in some time or after particular events.
However, everyone who has looked into it seriously knows that many investing approaches may vary strongly. And the quality and proper usage of these approaches are debated heavily.
One way to categorize different styles of investment is by risk-tolerance. Investors may choose the conservative, moderate or aggressive styles, depending on how much risk they are willing to tolerate, and this choice will partly determine which industries they will focus on.
Another way is to look at the methods used. There are traditional methods of investing, which in some sense could be called qualitative, when investors do most of their research and analysis themselves, concentrating on a rather limited amount of information. In contrast, there are quantitative methods of investment, which employ algorithms to build investing models which should calculate the best investment opportunities from much more data.
Data-driven investing can be understood as a step further from the latter approach. Quantitative investment models are also data-driven, generally speaking. However, quant investment models mostly use historical data to build and calibrate investment formulas. The main idea behind data-driven investment is utilizing various alternative data sources. This leads to investment decisions that are entirely up to date in relation to the data they are based on. Furthermore, using different types of data sources build well-rounded data strategies, meaning that investors are capable of taking into account more variables when making decisions.
That is why data driven-investing approach is said to unveil new possibilities to correct the weaknesses of previously introduced investing methods.
Advantages of data-driven investing
The fact that there are many different approaches and categories of investing styles shows that there is no clear consensus on which way is the best. It is too early to say at the moment whether data-driven investing will someday be recognized as such clearly best approach.
However, there are reasons to believe that this approach to investing has considerable improvements compared to traditional and model-driven investing. Here are some advantages of data-driven investment strategies.
1) Multiple perspectives. One of the main advantages of data-driven investment has already been hinted at. Utilizing multiple data sources for this investing style allows one to look at a particular company, market event, or industry situation from various perspectives. When all the data is analyzed, one arrives at a comprehensive picture of the situation, which allows one to apply the most reliable investing strategy in this particular case.
2)Predicting the unpredictable. Since most quantitative models use historical data, some outcomes are simply impossible to predict for these models. Data-driven investing broadens the limit of what can be predicted. Specifically, when we consider the amount of data that can be collected and the rate at which it is collected, we can begin to see that predictions can be made faster and more accurately than ever before. Additionally, the data-driven model enables almost as fast analysis of the projections, allowing for constant corrections and improvements to heighten its predictive capabilities.
3)Efficiency. Data-driven investment is merely more efficient than strategies based on different approaches. AI-based data analysis allows to handle more information and arrive at sufficient insights in less time. Saving time and manual labor also means cost-efficiency, thus next to the direct returns on their investments, investors also profit indirectly.
What is next?
Thus, it is clear that the potential of data-driven investment is high and well worth unlocking. Does this mean that the future of investment is data-driven?
Most likely, but this should not be understood as the removal of old, qualitative analysis and creative decisions by investors. Data-driven investment is an inherently hybrid model. It uses all the available data sources and as much information as possible. But finding out and creatively combining these sources is the task for financial analysts and investors, as are the final decisions based on the information provided by the data-driven model.
Therefore, we can expect the future of investing to be decided by people embracing big data analytics and expanding the limits of what can be achieved through it.
