Alternative data (finance)
Alternative data (in finance) refers to data used to obtain insight into the investment process. These data sets are often used by hedge fund managers and other institutional investment professionals within an investment company. Alternative data sets are information about a particular company that is published by sources outside of the company, which can provide unique and timely insights into investment opportunities.
Alternative data sets are often categorized as big data, which means that they may be very large and complex and often cannot be handled by software traditionally used for storing or handling data, such as Microsoft Excel. An alternative data set can be compiled from various sources such as financial transactions, sensors, mobile devices, satellites, public records, and the internet. Alternative data can be compared with data that is traditionally used by investment companies such as investor presentations, SEC filings, and press releases. These examples of “traditional data” are produced directly by the company itself.
Since alternative data sets originate as a product of a company’s operations, these data sets are often less readily accessible and less structured than traditional sources of data. Alternative data is also known as “exhaust data.” The company that produces alternative data generally overlooks the value of the data to institutional investors. During the last decade, many data brokers, aggregators, and other intermediaries began specializing in providing alternative data to investors and analysts.
Examples of Alternative Data
Examples of alternative data include:
- Geolocation (foot traffic)
- Credit card transactions
- Email receipts
- Point-of-sale transactions
- Web site usage
- Obscure city hall records
- Satellite images
- Social media posts
- Online browsing activity
- Shipping container receipts
- Product reviews
- Price trackers
- Flight and shipping trackers
Uses of Alternative Data
Alternative data is being used by fundamental and quantitative institutional investors to create innovative sources of alpha. The field is still in the early phases of development, yet depending on the resources and risk tolerance of a fund, multiple approaches abound to participate in this new paradigm.
The process to extract benefits from alternative data can be extremely challenging. The analytics, systems, and technologies for processing such data are relatively new and most institutional investors do not have capabilities to integrate alternative data into their investment decision process. However, with the right tools and strategy, a fund can mitigate costs while creating an enduring competitive advantage.
Most alternative data research projects are lengthy and resource intensive; therefore, due-diligence is required before working with a data set. The due-diligence should include an approval from the compliance team, validation of processes that create and deliver this data set, and identification of investment insights that can be additive the investment process.
Alternative data can be accessed via:
- Web scraping (or web Harvesting, performed by computer programmers that design an algorithm that searches websites for specific data on a desired topic)
- Acquisition of Raw data
- Third-party Licensing
In finance, Alternative data is often analysed in the following ways:
- Scarcity: the data Information overload within financial markets
- Granularity: the level of detail and aggregation of data (including time)
- History: the trajectory of data
- Structure: the form of the data (csv, json etc.)
- Coverage: the stocks or geographical locations that data can be linked with
While compliance and internal regulation are widely practiced in the alternative data field, there exists a need for an industry-wide best practices standard. Such a standard should address personally identifiable information (PII) obfuscation and access scheme requirements among other issues. Compliance professionals and decision makers can benefit from proactively creating internal guidelines for data operations. Publications such as NIST 800-122 provide guidelines for protecting PII and are useful when developing internal best practices. Investment Data Standards Organization (IDSO) was established to develop, maintain, and promote industry-wide standards and best practices for the Alternative Data industry.
- Review of the terms and conditions associated with the websites crawled
- Control over the potential interference with crawled websites
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