The Rise of Alternative Data: How It‘s Revolutionizing Investing and Financial Markets

In the world of finance, information is power. Investors are always searching for an edge – a nugget of insight that can help them make smarter decisions, uncover hidden opportunities, and beat the market. Increasingly, that edge is coming from alternative data.

Alternative data refers to any non-traditional data used to gain insights into investment opportunities. Unlike conventional financial data (such as SEC filings, earnings reports, and market prices), alternative data comes from a wide variety of sources, many of which are outside the realm of finance. This could include satellite imagery, social media sentiment, credit card transactions, web scraping data, and much more.

The alternative data industry has exploded in recent years as investors seek new ways to gain a competitive advantage. According to AlternativeData.org, the number of alternative data providers has grown from just over 100 in 2008 to over 1,500 today. And spending on alternative data is expected to exceed $17 billion by 2027, up from just $1.1 billion in 2019 (Source: Research and Markets).

So what‘s driving this growth? Put simply, alternative data provides investors with a more comprehensive, real-time view of companies, markets, and economies. By leveraging insights from non-traditional sources, investors can spot trends, risks, and opportunities that may not be apparent in conventional financial data.

The Varieties of Alternative Data

One of the key features of alternative data is its diversity. There are countless types of alternative data being used in finance today, each offering a unique lens on business and economic activity. Here are some of the most common categories:

Web Crawled Data: Data extracted from websites and online platforms, such as product prices, inventory levels, web traffic, search trends, job postings, and more. Web crawling can provide granular insights into company performance and consumer behavior. According to a report by Opimas, web crawled data is the most widely used type of alternative data, employed by 71% of asset managers (Source: Opimas).

Social Sentiment Data: Analyzing social media posts, news articles, blogs, forums, and other text-based sources to gauge public opinion about a company, product, or market. Natural language processing (NLP) and machine learning techniques are used to quantify sentiment and identify key themes. Social data can help predict shifts in consumer behavior and brand perception. A study by Greenwich Associates found that 34% of asset managers are using social sentiment data (Source: Greenwich Associates).

Geolocation Data: Data on the physical location and movement of people and assets, gathered from GPS-enabled devices, Wi-Fi networks, and other sensors. Geolocation data can reveal foot traffic patterns, supply chain movements, and industrial activity. It‘s used heavily in the retail and real estate sectors to assess company performance. 31% of hedge funds use geolocation data, according to EY (Source: EY).

Transactional Data: Data on consumer and business transactions, such as credit card purchases, online orders, and point-of-sale data. Transactional data provides a high-frequency view of revenue growth, market share, and consumer spending patterns. Bloomberg reported that 24% of hedge funds are using credit card data (Source: Bloomberg).

Satellite Imagery: High-resolution images captured by satellites, drones, and other remote sensing devices. Satellite imagery is used to estimate commodity production, track industrial activity, measure economic growth, and more. The number of satellite imagery vendors has grown 5x since 2016, according to AlternativeData.org (Source: AlternativeData.org).

To put the scale of alternative data into perspective, consider this: each minute, consumers spend $1 million online, YouTube users watch 4.5 million videos, and 41.6 million messages are sent on WhatsApp and Facebook Messenger (Source: Visual Capitalist). All of this activity generates vast troves of data that can be analyzed for investment insights.

Why Alternative Data Matters for Investors

The appeal of alternative data for investors is simple: it provides a potential information edge in an increasingly competitive market. By harnessing non-traditional data sources, investors can gain insights that aren‘t available through conventional channels.

One of the key advantages of alternative data is its timeliness. While traditional financial reports are released on a quarterly or annual basis, alternative data is often available in real-time or near-real-time. This allows investors to track company performance and market trends as they unfold, rather than waiting for official disclosures.

Alternative data also offers a more granular view than traditional metrics. For example, while earnings reports might show overall sales growth, web data can reveal which specific products are selling well. Geolocation data can show how traffic to retail stores changes day by day or even hour by hour.

This level of detail is extremely valuable for investors seeking to understand the underlying drivers of company performance. By combining multiple alternative datasets, investors can develop a comprehensive mosaic of a company‘s operations and market position.

And the proof is in the pudding. Numerous studies have shown that alternative data can provide a significant boost to investment returns:

• A study by Greenwich Associates found that quantitative funds using alternative data outperformed those that didn‘t by 6% per year (Source: Greenwich Associates)
• Hedge funds using alternative data had a Sharpe ratio (a measure of risk-adjusted returns) 25% higher than those that didn‘t, according to EY (Source: EY)
• 71% of asset managers believe that alternative data provides an edge over competitors, according to a survey by Lowenstein Sandler (Source: Lowenstein Sandler)

Of course, alternative data is not a silver bullet. It comes with its own set of challenges and risks, which we‘ll explore later. But for investors willing to put in the work, the potential rewards are significant.

Putting Alternative Data to Work

So how exactly are investors using alternative data to inform their decisions? Let‘s look at a few real-world examples:

Predicting Earnings Surprises: Earnings announcement days are some of the most volatile trading periods, as investors react to whether companies beat or miss expectations. Alternative data can help predict these surprises in advance. For example, satellite imagery of retail parking lots can reveal foot traffic trends that foreshadow sales growth. Similarly, sentiment analysis of social media chatter or online job reviews can provide clues about a company‘s future performance.

In one notable case, the investment firm Thasos used geolocation data from mobile phones to predict that Chipotle would beat earnings estimates by analyzing foot traffic to its stores. The stock surged 10% when Chipotle‘s strong results were announced (Source: CNBC).

Tracking Supply Chains: Alternative data can provide valuable insights into companies‘ supply chains and logistics. By monitoring suppliers, shipments, and inventory levels, investors can gain a real-time view of potential disruptions or efficiency gains.

For instance, investors have used satellite imagery to track activity at mines and oil wells, using the data to estimate future production levels. Shipping container data and bill-of-lading records can reveal changing trade volumes. Even online job postings can signal a company‘s expansion plans or hiring challenges.

Monitoring ESG Factors: Environmental, social, and governance (ESG) factors are becoming increasingly important for investors. But traditional ESG metrics can be backward-looking and rely on self-reported data from companies. Alternative data can provide a more objective, real-time view.

Satellite data, for example, can track pollutants like nitrous oxide emissions or oil spills. Web scraping can be used to check for labor violations in global supply chains based on NGO reports or worker complaints. NLP analysis of earnings call transcripts can quantify the emphasis management places on ESG initiatives.

Informing Real Estate Investments: Alternative data is transforming the way investors assess property values and rental yields. Geolocation data can reveal foot traffic and commuting patterns around a property. Transactional data can provide insight into rental payments and occupancy rates. Even social media activity and online reviews can be used to gauge tenant satisfaction and property maintenance.

Firms like WeWork and AirDNA are using alternative data to identify profitable investment opportunities and guide development projects. By combining traditional property data with alternative sources, investors can develop more accurate valuation models.

These are just a few examples of how alternative data is being deployed in practice. As the field matures, we can expect to see even more innovative applications across different asset classes and investment strategies.

Overcoming the Challenges of Alternative Data

For all its potential, alternative data also comes with significant challenges. Investors need to be aware of these risks and take steps to mitigate them.

One of the biggest challenges is data quality. Unlike traditional financial data, which is typically audited and standardized, alternative data can be messy and unstructured. It may be incomplete, inconsistent, or prone to errors. Investors need to carefully vet data sources and develop robust cleansing and normalization processes.

Privacy is another key concern. Much of the alternative data being used today is generated by individuals who may not be aware their data is being collected and sold. There is growing regulatory scrutiny around data privacy, with laws like GDPR in Europe and CCPA in California imposing new restrictions on data usage.

Investors need to ensure they are sourcing data legally and ethically. This means working with reputable data providers, obtaining necessary consents, and anonymizing personally identifiable information.

Integrating alternative data into investment workflows can also be challenging. The sheer variety and volume of alternative data can be overwhelming, and not all of it will be relevant for a given strategy. Investors need to develop a clear data sourcing and management plan, with the right tools and expertise to handle unstructured data.

Some key best practices for working with alternative data include:

• Clearly define your investment objectives and data requirements upfront
• Conduct thorough due diligence on data providers, including quality checks and backtesting
• Ensure compliance with data privacy regulations and ethical guidelines
• Invest in secure, scalable data infrastructure to handle large, diverse datasets
• Employ data scientists and analysts who can wrangle unstructured data and extract actionable insights
• Continuously monitor data quality and refresh models as new data becomes available

By taking a disciplined, proactive approach to alternative data, investors can navigate the risks and unlock the potential rewards.

The Future of Alternative Data

As alternative data goes mainstream, we can expect to see continued growth and evolution in the space. More and more investors will embrace alternative data as a core part of their strategies, and spending on data acquisition and analytics will rise.

We‘ll likely see further consolidation in the alternative data industry, as leading providers merge to offer end-to-end solutions. At the same time, new startups will emerge to offer niche datasets and innovative analytics.

There will also be a growing focus on data quality and standardization. Industry groups like FISD and IDSA are working to develop common standards and best practices for alternative data. This will help improve data reliability and comparability across providers.

As investors become more sophisticated in their use of alternative data, we can expect to see more advanced analytical techniques like machine learning and artificial intelligence deployed at scale. This will enable investors to extract even more granular insights from large, complex datasets.

We may also see alternative data expand into new asset classes and markets. For example, private equity and venture capital firms are starting to use alternative data to assess startups and guide investment decisions. And as emerging markets develop more robust digital infrastructures, alternative data could provide valuable insights into economic growth and consumer behavior.

Of course, the regulatory landscape around alternative data will continue to evolve as well. Policymakers are taking a closer look at data privacy and security issues, and new regulations could impose additional compliance burdens on investors and data providers.

But despite these challenges, the future of alternative data looks bright. As Tammer Kamel of Quandl put it, "Alternative data is not just a passing fad or a short-term phenomenon. It represents a secular shift in the way investors think about data and make investment decisions."

In other words, alternative data is here to stay – and its impact on financial markets will only continue to grow in the years ahead. For investors who can harness its power, the potential rewards are vast. But it will take a combination of technical expertise, domain knowledge, and ethical judgment to truly succeed in this new data-driven era of finance.