With alternative data on the rise, various data vendors have begun to provide services and offerings that allow retail investors to gain an edge in the market. Pulling from various sources like financial trades, sensors, PDAs, satellites, reports, and the web, investors can now use alternative data to make better business decisions that can create alpha.
Use cases for alternative data
The use cases of alternative data are plentiful, from more short-term uses such as identifying signals via sentiment analysis or social media to long-term revenue predictions. There is money to make everywhere, and anywhere there is money to be made, you can use alternative data. Monitoring web data such as social media conversations or product reviews can provide nuggets of information, which can then be used to trade and make money.
There are boundless prospects and kinds of elective information out there. One major use case of alternative data is gaining predictive insights from company’s quarterly results. Anticipating results can help with short-term turnarounds.
Other examples include looking at transaction data, app data and receipts. This can help to understand a company better, which then add to making investment decisions off the company’s performance.
Examples of alternative data
Alternative data comes from unconventional sources. The following data sources are just some examples of alternative data:
- Geolocation (foot traffic)
- Credit card transactions
- Email receipts
- Point-of-sale transactions
- Mobile App or App Store analytics
- Obscure city hall records
- Satellite images
- Social media posts
- Online browsing activity
- Shipping container receipts
- Product review
Advantages of using alternative data
Alternative data analyzes financial patterns, including short, middle, and long-haul patterns. Collecting huge amounts of alt data and analyzing it to understand better how the market works can create huge upsides for investors.
Moreover, as AI becomes more democratized, retail investors are gaining access to the power of giants, being able to leverage machine learning models to receive more predictive insights, examining more than just the financial industry but air travel, medical care, and more.
In the time of digitization and with the improvement of advancement at the speed of light, ventures that are seriously controlled through guidelines, similar to record and banking, consistently endeavor to keep their foundation on top of contemporary requests. Hence the requirement for alternative data has increased considerably.