Leveraging Alternative Data for Alpha Generation in Investment Strategies
Version: 1.0.1
Alternative data is becoming increasingly important in investment finance as analysts strive to beat the benchmark index and overall market. Alpha refers to the excess return relative to the benchmark, adjusted for risk.
What is alternative data?
Traditional data includes corporate filings, analyst predictions, and ticker data.
Alternative data is non-traditional data. It can come from various sources in both structured and unstructured formats. Examples include ESG data, transaction data, web traffic, media sentiment, social media sentiment, and sensor data, among others.
Common Alternative Data Types
- Transactional Data - Credit Card Transactions, POS & E-commerce
- Geospatial Data - Satellite Imagery, Geolocation, Aerial Imagery
- Web and App Data - Web Traffic, App Usage, Web Scraping
- Social and Sentiment Data - Social Media Posts, Product Reviews & Sentiment Analysis
- Sensor and IoT Data - Internet of Things Data, Weather Data & Traffic Data
- Public Records and Government Data - Government Contracts, Regulatory Filings
- Environmental, Social, and Governance (ESG) Data
- Human Mobility and Demographics
Data Governance and Compliance
Alternative data comes with its own set of risks, which is why having strong governance and compliance policies and procedures will help mitigate those risks. Establish the following best practices to ensure data quality and regulatory compliance:
- Clear policies and procedures
- Data Ownership
- Audits and Assessments
- Training and Awareness
- Data Quality Automation
Example Alternative Data Strategies to Generate Alpha
-
Brand Value Factor Strategy
This is used to identfy companies with low brand value and can be calculated from a number of alternatives data sources. Examples include:
- Sentiment Analyses - Using social media commentary to gain insights and gauge sentiment.
- Transaction Data - Analysising spending patterns
- Brand Recall Rate - Measures the effectivness of a brand’s presence
-
Technology Momentum
This involves examining the growth and impact of technological trends. Examples include:
- Search Trends - To measure public interest
- Patent Databases - To track innovation
- Job Market Data - To analyse talent demand
-
Employee Review Sentiment Analysis
This involves using data from the likes of Glassdoor.
- Natural Language Processing - Analyses of employee sentiment and company culture.
This is just an example of the analyses available in strategies to deliver alpha. They can be combined and used with traditional data sources to provide greater insight into a market, company, or country.
Alternative data is often large and unstructured and requires intensive steps to get it into a useful form, this can include, mapping, cleaning, and aggregating.
Conclusion
It’s clear that the alternative data sources can provide valuable insights. According to Blackrock[1], during the first half of 2020, Blackrocks internal signal library showed that alternative data signals had an average IR of above 1, compared to 0.2 for traditional data signals. Alternative data is growing rapidly in the alpha generation space with the alternative data market expected to grow at a compounded annual growth rate of 28%[2].