Investors make some of the most important decisions in their life by looking at the data on stocks and businesses. The variety of this data is tremendous since traditional financial data is now supplemented by alternative data sources. These sources can be anything from mobile devices to social media and they produce huge loads of valuable information. But to make use of this information investors have to apply the data analytic approach to its fullest potential. Drawing insights from data requires skill and knowledge of various kinds. But the fruits that skillful data analysis produces are especially sweet for data-minded investors.
The steps of drawing insights from data
The road from data to insights is quite long and full of obstacles but truly worth taking. Especially when you need to make a decision with a big chunk of your or your client’s financial resources on the line.
Thus, investors and hedge fund managers aim at drawing insights from data with every new opportunity for a profitable financial move. It can be summarized as a step-by-step process, although each stage is itself comprised of many minor tasks that need to be performed.
The first step is of course getting the data. Investment funds these days try to utilize as many sources of data as possible. Alternative data sources provide much-needed supplements to the more common information gained from company statements and financial reports. While financial firms might want to have an in-house team for data gathering, due to the variety and versatility of alternative data, using third-party data providers is often necessary.
The next step is concerned with data management and structuring. Data can already be structured or semi-structured, but quite often it comes in raw. Structuring raw data is a very important stage of the procedure as one can add quality control to it. Data quality is crucial to drawing insights from data as your final conclusions will only be as reliable as your initial data sets.
One can also mention algorithm training and computer modeling as possible steps in the road. Investors have been utilizing machine learning and other AI-related processes for quite some time now and with astonishing success. This way data is turned into insights by seeing what algorithms can predict based on it and how their forecasting capabilities improve with training.
In any case, any form of data analysis inevitably leads to the final stage of drawing insights from data which is reporting the results. There are also various tools to help with this step. The conclusions of the analysis need to be published and presented in the clearest and most understandable manner possible. This is where visualization tools or natural language processing software can help.
When the data-based insights are reported to the investors and executives with utmost clarity, they are prepared to develop a reasonable investment strategy.
The importance of data analytics in investment decision-making
Data provides an opportunity to arrive at the most important investment insights that can form bases for very profitable financial strategies. It is achieved through data analytics which is the sum total of all the tools and methods used for drawing insights from data.
The benefits of utilizing the most state-of-the-art analytics for investment decision-making are multiple. Here is an outline of why it is so important to be insight-driven in the world of finance.
1) Opportunities are recognized on time. Data analytics provide the most efficient way to forecast the future success of all kinds of stocks. New and promising start-ups first show up on the investor’s radar through alternative data. Some social media buzz behind a relatively unknown product or high level of technological innovation can be the first signs of future greatness. Data insights allow seeing these signs as soon as possible.
2) Bias is removed. All humans are biased toward something on some level. This is an unavoidable problem with making decisions based on gut feeling. Investors and hedge fund managers cannot afford to risk bias in such important matters. Drawing insights from data allows making decisions that are supported by solid evidence. Thus, a gut feeling can be checked and supported or adjusted based on what the data tells us.
3) Improvements can always be made. No investment model is ever perfect. However, a data-based strategy can always be improved by adding more information or looking at it in a different way. Thus, investment models based on data are very scalable and flexible – add more data and they will give you a more accurate prediction. This way investors are provided with a clear path of constant advancement and growth of profits.
4) More ground can be covered. Data analytics provide an opportunity for investors to look into new territories. With the help of AI tools, investors can look at data from various industries and locations. By efficiently covering more markets investors are able to branch out and find unexpected ways to diversify their portfolios. Aside from mitigating risks, this opportunity simply makes the investment even more interesting and exciting.
Thus, drawing insights from data is one of the most important aspects of contemporary investing. Decisions based on these insights are more reliable and can be made faster than ever before. All these benefits lead more and more financial firms toward a data-driven approach. The key thing to remember is that data is the first step, but what one truly should aim for is insight-driven decision-making.
