Given the recent pandemic’s uncertainty and disturbances, it is not surprising that investors seek more information before making a decision. Although alternative data is not new, it has been the recent focus for many investing firms. A recent study concluded that the global alternative data market size would grow at a 44% CAGR from 2020 to 2026, reaching an impressive $11.1 billion. The following sections explore the importance of alternative data and its predicted trends this year.
Alternative data datasets contain any type of information that is not typically enclosed in traditional sources, such as financial reports or SEC filings. For instance, any information sourced from websites, web traffic, satellites, sensors, social media, or cell phones are considered alternative data.
This information is now increasingly being used by investors to make better investment decisions. There is only one purpose for using these data: to have better insight into the markets and boost portfolio returns.
Before 2020, the prominent role of using alternative data was to make better and more profitable long-term decisions, while ESG also had an upward trend. Despite this, as the pandemic changed the world as we knew it, investors have started to use alternative data for an entirely new purpose: immediate risk management. As businesses struggled to remain open, the workforce turned to remote work, while investors actively sought alternative information to better understand market volatility from different perspectives.
Alternative data has already been used by hedge funds for some years now. Still, there is evidence that it is quickly expanding to numerous other industries, including energy, retail, transportation and logistics, and more. Machine learning methods have also been on the rise due to investors’ interest in collecting and analyzing large datasets.
One of the recent emerging trends refers to consumption data analysis. This offers transaction-related information to investors that can help them predict business sales, so it is not surprising that this trend is expected to spike in 2021 and beyond.
Although leveraging machine learning methods is not so mainstream just yet, early adopters can benefit from major advantages. For example, in 2018, it was rumored that Cambridge Analytica collected information from 50 million Facebook profiles to use in the Trump presidential campaign back in 2016. Despite this, Facebook’s stock price did not experience any slowdown until later that year – primarily due to investors’ reaction to Facebook’s announcement that user growth is slowing down.
In other words, investors using alternative data can identify these events and act on them before the general market, simply because most investors are pretty inefficient when it comes to digesting unstructured information. Those who are proficient in machine learning can determine which events will impact the stock price, resulting in higher returns.
ESG has become a significant point of interest for investors, especially as policymakers, such as the European Commission, have proposed different methods to improve the integration of sustainability factors in the investment decision-making process.
In 2021, it is expected that this focus will increase, along with individual investors’ interest in sustainability. For example, 64% of active retail investors focused on sustainable investment funds in 2017 compared to 2012, according to a study.
However, generating profits with ESG strategies has become more difficult since most investors have access to the same resources: the company’s sustainability reports. Another issue of this traditional source of data is that the company itself reports the information, so it may not reflect the reality. In 2021, investors are expected to become creative and start using alternative data, such as social media information, to discover unique signals and create profitable investment strategies.
Alternative data have always been quite fragmented, coming from a wide variety of sources. In 2021, it is expected that this information will turn into a more organized mass of data as alternative data providers step in to offer quality, cleaner datasets.
For example, investors who focus on certain types of stocks, such as retail, may want to access alternative data relevant to the particular industry, combining geolocation information with transactions and social sentiment. Combining these different datasets into a curated, well-presented form can provide a significant advantage.
Even more, this aggregation of alternative data can define more clearly the previous uncertain international market opportunities. In other words, combining different datasets can make emerging markets, such as China, more transparent and safer for investors. This aggregation allows investors to remain informed at all times and keep up with international market opportunities.
All in all, there is no surprise that alternative data is on the rise. In a world driven by uncertainty and volatility, more and more investors seek alternative data datasets that offer them a glimpse into information that is not widely available. This provides a competitive advantage that helps find the alpha and drive higher returns than the market.