Trading With Alternative Data

Back in the late 2000’s I used to share an office with an options trader.

We rented this cool office in a glass building and traded all day long. Fun.

During downtime, we would talk about markets, risk and anything to do with trading.

One time, he shared with me this story about an Australian trader who would pay locals in developing countries to monitor specific gold mines.

Their job was to count the trucks entering and leaving the mine.

And with that info, this trader could work out how much gold they were mining, and then calculate the revenue of the company.

Then of course he’d use that to trade with.

The perfect scenario would be an undervalued asset trading at lows, that he knew had mined way more gold than expected, he could build a position before earnings and make bank when the price popped.

Some might cry insider trading – but if you think about it, this information is readily available, it’s not secret. It’s just that this trader had the mind and resources to convert it into actionable info.

Now, I don’t know how much truth is in this story. (You know how traders like to exaggerate “Yeah bro I bought size at the low print…”)

But that was the first time I’d heard about so-called “Alternative Data”.

Using data other than traditional, price, earnings or economic indicators to make decisions.

And it’s a big business:

Currently worth $7.2bln it’s predicted to skyrocket to $135bln by 2030 as hedge funds try and find new ways to extract alpha.

(As a side note if you’ve got a cool idea for an alternative data company, let me know, I want to invest.)

Current examples of alternative data include:

• Satellite Imagery: Used for tracking changes in infrastructure or agricultural yields.
• Social Media Sentiment: Analyses consumer sentiments and trends from social media platforms.
• Credit Card Transactions: Provides insights into consumer spending patterns.
• Mobile App Usage: Tracks user engagement and popularity of mobile applications.
• Geolocation Data: Monitors foot traffic and mobility trends at specific locations.
• Web Scraping Data: Collects data from websites for price monitoring, product changes, or sentiment analysis.
• Email Receipts: Aggregates consumer purchase data from emailed receipts.
• Internet of Things (IoT) Data: Uses sensor data from connected devices for various predictive analytics.
• Supply Chain Data: Monitors logistics and supply chain movements to gauge economic activity.
• Consumer Reviews and Feedback: Analyses customer reviews for sentiment and product feedback.

And I’m sure there are many examples that have confidentially agreements and single contracts with large firms that we won’t hear about…

So how can retail traders take advantage?

Well, many of these services are prohibitively expensive for most, but companies like Quiver Quant are bringing alternative data like congress trading to individual traders at accessible prices.

And I’m sure there will be more.

This is just capitalism at its finest… set the rules of the game and watch the market solve for X.

Love it.