Amidst the ever-changing world of quantitative investing, investors continue to seek alpha in new places outside standard financial data points. The significance of alternative data for hedge funds in order to get an edge could not have been more valued as we advance into 2024. Read on for a look at some of the alternative data sources incipient to quant investors as they continue feeding their strategies and alpha-generating programs.
1. Satellite Imagery and Geospatial Data
As such, satellite imagery has become an important method to quantify the real-time state of economies for quant investors. High-resolution images can offer beneficial details of;
Retail foot traffic
Agricultural crop yields
Oil storage levels
Construction progress
Supply chain movements
Orbital Insight and Descartes Labs are out of the lead to create actionable intelligence from space-based data. Hedge funds, for instance, used satellite photos to count the number of cars in retailer parking lots as a read on sales results and were frequently able to get such waypoints weeks ahead of official earnings reports.
2. Social Media Sentiment Analysis
Moods extracted from crowds in social media can have predictive powers about rising or dropping prices on e-commerce internet markets. Today, cutting-edge natural language processing (NLP) algorithms can process millions of social media posts within minutes in order to identify whether a company, product, or even an economic event excites dismay.
Sites such as StockTwits and TickerTags gather and analyze conversations on social media pertaining to financial markets specifically. The data is already being used by quant investors…
Anticipate the mechanically limited term price changes.
Measure brand health and satisfaction with the user experience
So by doing that, it can find new trends or emerging crises.
3. Alternative Credit Data
Credit scores in the traditional financial sector are no longer limited to them. We are now seeing that this idea of consumer or business financial health is more nuanced when analyzed via alternative credit data sources. These include:
Utility bill payment history
Rent payment records
Mobile phone usage patterns
Social media activity
That data is making its way into the credit risk models at companies like Equifax and Experian. This data could be very insightful for quant investors in understanding consumer behavior and economic health on a more granular scale.
4. Internet of Things (IoT) Sensors
IoT devices are everywhere now, producing an enormous stream of tiny real-time data that can provide invaluable input into investment algorithms. Some applications include:
Advanced electricity meters with live energy use statistics
Driving behavior and vehicle use can offer valuable data points from connected cars
Smart factories with Industrial IoT sensors tracking manufacturing output and efficiency
This real-time granular data can act as an early signal of economic trends or whether company performance may be above, below normal and ultimately facilitate a leg up on macro decisions for quants.
5. Web Scraping and Alternative Web Data
These days, investors are now able to harness more sophisticated web scraping techniques thereby being enabled to gather some of the most valuable data available on the internet. Here are some of the highlights:
Banking and E-commerce: pricing & inventory data;
Job listing trends
Patent filings
Online product reviews
For instance, when web-scraping for investments there are specialized companies such as Thinknum and Quandl that collect the data in a standardized way. Customer Ask.Skill: Identify trends in real-time data (incoming customer demand, company hiring, competitive positioning)
6. Mobile Device Location Data
Miranda L, 2018 — Location data from mobile phones gives insight into consumer activity and economic trends [Medium] Applications include:
Retail Foot Traffic Analysis
Tracking migration patterns
Tracking supply chain movements
Location data is especially sensitive, but companies like Foursquare and SafeGraph have found ways to create valuable derived insights from this type of aggregated anonymized location without running afoul of privacy regulations.
7. Environmental, Social, and Governance (ESG) Data
With growing interest in ESG factors from investors, new alternative data sources are cropping up to give a more holistic and real-time overview of the corporate sustainability landscape. These include:
Data on carbon emissions coming from IoT sensors —
Platform-driven employee sentiment analysis (e.g., Glassdoor)
Sustainable Supply Chain Monitoring Parameters
In contrast, Truvalue Labs does machine learning based on anything in the public domain — news sources, NGOs social media, etc., to pull real-time data into an ESG scorecard.
Challenges and Considerations
Although the power of alternative data sources is an exciting prospect for quant investors, these same tools also introduce their challenges:
Data Quality and Consistency – The quality of alternative data sources has to be maintained so that the entire system can function with reliability and consistency.
Essentially Mixing Apples to Oranges: Integrating the alternative data as with traditional financial metrics requires very advanced types of Data Integration and Analysis techniques.
Regulatory Compliance — Understanding the increasing challenges with data privacy regulations, especially as it pertains to personal data.
There are a lot of data, so the signal-to-noise ratio is low.
Cost: Acquiring and processing alternative data has a cost associated with it, therefore the overall investment should be evaluated on an incremental basis
Conclusion
We now enter 2024, the land of fish freedom trees, and alternative data in which quant investing is booming like nowhere else. It is those quants who can use these heterogeneous sources of data (injecting them into their investment processes) that are likely to be the most successful investors going forward, despite — or perhaps because of — myriad challenges encountered along this path.
When you put together classical finance research and modern alternative data for quantitative investing, these quants are in a position to realize unique rewards over the future very crowded industry landscape. Nevertheless, like any investment strategy doing proper due diligence and testing that for sure it meets your expectations is critical to being successful in the world of quantitative investing over a longer period.