What Does It Take to Make Timely Trades on Global Investments? Hyperlocal Data, and Lots of It

Two factors make all the difference between global trading triumphs and misfires: timing and accuracy. 

Financial analysts have to be quicker than their competition in assessing opportunities and then acting on them, and those decisions must be informed and supported through a careful study of reliable and relevant data.

But what if you’re working with incomplete or outdated information? You might pull the trigger on an investment that’s no longer beneficial to your fund’s performance, or your model might execute a trade when conditions for arbitrage no longer exist. 

That’s why having data that is both continuous and hyperlocal is so valuable – especially if you’re operating in global regions where data is scarce or unreliable.

Let’s look at three ways continuously streamed, hyperlocal data can give global market analysts the edge.

Revealing risks that may not be as obvious at a macro level

An important priority for all financial analysts is being able to calculate risk—and let’s face it, that can be tricky business in a volatile and fast-changing world.

Hyperlocal, continuous data gives you an early and accurate window into situations on the ground such as political and social instability or military conflict.

This was the case a year ago when FilterLabs was monitoring Russian data to understand the impacts of the Wagner Group insurrection, led by Yevgeny Prigozhin. We were able to monitor media and social media discourse in different regions of Russia to show an initial positive spike in Progozhin’s popularity followed by a return to normal—and in some cases a negative drop—as Kremlin propaganda took hold.

Financial analysts monitoring this continuous stream of locally sourced data were able to make intelligent, accurate predictions that Prigozhin’s insurrection would fail, and the risk of further global economic destabilization would abate.

Of course, Russia is just one of dozens of countries embroiled in military conflict, and that’s in addition to the hundreds of other volatile situations related to religious differences, racial or ethnic tensions or political upheaval. When you have a steady source of data direct from the communities where these events are taking place, you can effectively determine risk and make decisions accordingly.

Identifying local patterns that may impact broader commodities markets 

Hyperlocal data collected from a broad range of conversational and behavioral sources can tip you off to changes in key commodities markets. For instance, traders of precious metals derivatives in India can get a read on local political conditions and tensions, as well as economic health and inflation—all of which impact supply and demand. 

Community-level data also tip you off to local disruptions or expansions in mining of high-value metals, as well as societal influences that boost consumption. India, in particular, experiences a noticeable bump in purchases of gold and silver during festivals and wedding seasons, which can push prices higher. (The extravagant recent wedding of Indian billionaires Anant Ambani and Radhika Merchant might single handedly have that effect!)

This holds true for other Indian commodities as well. By watching local data patterns, you can detect when an upcoming festival is boosting demand for agricultural products like oil, grains, sugar and spices. Also, hyperlocal construction data can let you act quickly when demand increases for cement, sand and gravel.

Getting access to local data brings patterns like these into sharp focus, rather than forcing you to extrapolate relevant information from broad, national data that may not apply to your specific commodities of interest.

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Providing early signals of changing conditions 

If there’s one thing most traders hate, it’s surprises. You need to know right away when conditions are changing so you can stay ahead of the curve, make decisive moves and beat the competition. 

That’s where a continuous stream of hyperlocal data can strengthen your hand. Feeding this data into your trading models can provide early detection when conditions are changing in a particular region, industry or commodity.

We recently noticed this when gathering data about inflation in China. Official reports were heralding stable inflation and strong economic health. But FilterLabs’ hyperlocal data picked up much more negative sentiment. Residents expressed anxiety about the distressed real estate and infrastructure sectors, bankrupted companies and shrinking personal assets. Financial analysts with an eye on China appreciated this specific and accurate temperature check on China’s economy. 

The same thing can happen when you’re looking at areas facing war, contentious elections, labor strikes and even natural disasters. Data that reveals what local residents are saying and doing tells you immediately when something is shifting, so you can make evidence-based decisions that advance or protect your investments.

Don’t Stop at Standard Sources

Hyperlocal data gets you closer to the action. Continuous data makes sure what you’re seeing is current. But there’s one more important ingredient: high-quality data sources. Many traders have their pulse on foreign media and social media, but what bridges the gaps in understanding are less typical sources that reveal unfiltered, authentic conversation and behavior. 

At FilterLabs, we use regional and subject matter experts to uncover unique data sources, including personal and professional blogs, community chat rooms and local employment and consumption reports. When fused with large volumes of social media and news media, this data stream becomes a rich source of market intelligence for global market analysts.

If you’re interested in supplementing your current data sources with continuously streamed, hyperlocal data, reach out for a conversation. We provide data as you need it: seamlessly integrated with your existing models, or presented as curated insights via the Talisman Dashboard.