Investing with Big Data

Big Data: How new technologies are creating new ways of investing

What is “Big Data”?

Big Data refers to the management and analysis of vast quantities of data that cannot be processed using ordinary techniques, since they exceed the “conventional” volume and capacity limits. These new techniques also make it possible to analyze a wide variety of types of data, such as images and digital forms, audio files, satellite images, cell phone signals, internet searches, etc.
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Where does this “Big Data” concept fit into the world of investment funds? 
New technologies are making it possible to access new and different forms of data, from a wide variety of sources, which supplement the traditional analysis of investments. The goal is to help with decision making, providing new perspectives that enrich this analysis. 
In recent years, around the world we have seen a substantial interest in this field in the field of investment, which has substantially increased its technological capacities and the resources dedicated to these big data techniques. The goal of all of this is to discover and exploit market inefficiencies that help to obtain more attractive and consistent returns.
What types of Big Data techniques are used in investment funds? 
Some of the most common techniques include: processing natural language using computational reading (machine reading), pattern recognition (machine learning) and measuring internet search activity to predict changes in sales volumes. 
An example of these new techniques used in decision making is the measurement of investor sentiment through text analysis. A few years ago, this technique measured investor sentiment with a ratio between positive and negative words. Subsequent “machine learning” studies have proven that it is more effective to measure it according to who is speaking - the CEO is always more positive, whereas the Chief Financial Officer is usually less positive - and how they are saying it - what verbal tenses are being used: talking in the present is always more positive than talking in the future, which is usually negative, or how vague a speech is compared to one more focused on data, which is usually positive. In order to take these nuances quickly into account, in thousands of companies with several communications each year, we need powerful computer tools that analyze the information.
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To be taken into account:

  • This is a highly dynamic and experimental area, characterized by innovation, which means that there is a high number of changes in the models and measures applied.
  • The biggest risk of funds that are based on these types of techniques is the so-called “model risk”, which means that the investing process is based on the incorporation of new models which use these new data processing techniques. However, their effectiveness and suitability for the market conditions can vary significantly depending on the current market environment.
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