Ideas

Data has long been a precious commodity – yet it’s only getting more valuable.

At the beginning of 2020, the number of bytes in the digital universe was already 40X greater than the number of stars in the observable universe. 

Data is today’s “wild west” and the battlefield of today’s tech titans; with AI, The IoT, the Blockchain, and analytics leading the forefront. 

Alphabet, Amazon, Apple, Facebook, and Microsoft all have an unprecedented amount of data (and power).

Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect their data from prying eyes.

The trading industry has undoubtedly experienced the rapid growth of data, but it’s pervasive in every industry – and in our personal lives as well. 

Having basic data and basic analytics used to be enough, but the game is changing. Traders used to focus on price data, but now you’re seeing an influx of firms using alternative data sets to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable advantage. Understanding the game they’re playing (and the strategies and rules they follow are important), but now that’s just the table stakes.

Figuring out where you can find extra insight, or make the invisible visible, creates a moat between you and your competition – and lets you play your own game.

I shot a video in 2019 about Data as fuel for your business. Check it out.

 

 

It is interesting to think about what’s driving the new world (of trading, technology, AI, etc.), and that often involves identifying what drove the old world. History has a way of repeating itself.

Before e-mails, fax machines were essential. Before cars, people were pleased with a horse and buggy.

These comparisons contextualize the importance of data in today’s new world of economics and commerce.

 

via gapingvoid

Data as the New Oil

While not the best comparison, people often default to comparing data to oil. 

Since the Industrial Revolution, petroleum has played a pivotal role in human advancement. It fueled (and still fuels) our creativity, technology advancements, and a variety of derivative products. There are direct competitors to fossil fuels that are gaining steam, but it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.

The process of pumping crude oil out of the ground and transforming it into a finished product is far from simple, but anyone can understand the process at a high level. You have to locate a reservoir, drill, capture the resource, and then refine it for the desired product (e.g., heating oil, gasoline, asphalt, plastics, etc.). Then, you have to move it to where it’s needed.

The same is true for data.

You've got to figure out what data you might have, how it might be useful, you have to figure out how to refine it, clean it, fix it, curate it, transform it into something useful, and then how to deliver it to the people that need it in their business. And even if you've done this, you then have to make people aware that it's there, that it's changing, or how they might use it. For people who do it well, it's an incredible edge. – Howard Getson

Data can be seen as the fuel to the information economy and oil to the industrial economy. The amount of power someone has often correlates to their control of and access to resources … and diminishing or diluting those resources can lead to extreme consequences.

Why Data Is Better Than Oil

The analogy works, but it’s just that, an analogy. The more you analyze it, the more it falls apart. Unlike a finite resource (like oil), Data is all around us and increasing at an exponential rate.  So the game is a little different:

• Data is – ultimately – a renewable resource. It’s durable, it’s reusable, and it’s being produced faster than we can process it.
• Because it’s not a scarce resource, there’s no urge to hoard it – you can use it, share it, transform it, infinitely knowing that it won’t diminish. Data is more valuable the more you use it.
• As the world’s oil reserves dwindle (and renewable resources grow in popularity and effectiveness), the relative value of oil drops. It’s unlikely that will happen to Data.
• Also, while data transport is essential, it’s not expensive in the same way that transporting oil is. In fact, it can be transported and replicated at light speed.
• While petroleum can be transformed into many different products – the variety of data-related products and sources is basically infinite in comparison.

On Alternative Data

In the past, investors relied on information and experience from their real lives, from counterparties, and from fastidious attention to CNBC and stock tickers. 

However, fundamental discretionary traders account for just 10% of today’s trading volume. Quantitative investing based on machine intelligence and algorithms is the new normal.

While the games, the rules, and the players have all changed, the goal hasn’t… more alpha … more money … more reliably. 

Alternative data, to most, means tracking Twitter and Facebook sentiment, but confining your definition to that limits potential alpha. 

New sources of data are being mined everywhere, and are letting investors understand trends “before they happen.”

For example, mobile devices, low-cost sensors, and a host of new technologies have led to an explosion of new potential data sources to use directly for predictive insight or indirectly to help improve models.

In addition, private company performance, logistics data, and satellite imagery are becoming popular data sets in a data scientist’s alpha creation toolbox. 

There are often concerns about the cost and completeness of these datasets, but as we get better at creating and using them, both will improve. 

It also doesn’t always have to be confidential or challenging to find information. Traders now have access to vast amounts of structured and unstructured data. An important source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.

In the very near future, I expect these systems to be able to go out and search for different sources of information. It's almost like the algorithm becomes an omnivore. Instead of simply looking at market data or transactional data, or even metadata, it starts to look for connections or feedback loops that are profitable in sources of data that the human would never have thought of. – Howard Getson

In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often become slaves to the data, losing focus on the bigger picture. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution.

The thing about “sustainable alpha” is that while one might be able to achieve it, you can’t expect to have it doing the same thing everyone else does (or by doing what you’ve always done).

Markets change, and what worked yesterday won’t necessarily work today or tomorrow. Trading is a zero-sum game, and as we move toward the future, this only gets more apparent. 

The future of Data is bright, but it’s also littered with potential challenges. Privacy concerns and misuse of data have been hot button topics, as have fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.

The question becomes, how do you capitalize on data, without becoming a victim to it? 

Food for thought!