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How mapping geospatial data can provide market-moving insight

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Financial research analysts, portfolio managers and traders have been analysing time-series data for decades. In a world where milliseconds can equal millions of pounds, geospatial data adds a new dimension with significant implications for how decisions are made.

The case for data analysis in today’s financial services sector barely has to be made. Money is earned or lost based on rapidly changing information and the challenge for traders and analysts is to accurately recognise, analyse and predict those changes in real time.

Until recently, the benefits of using geospatial data - tied to some form of physical location-based tag - to understand fast-moving financial markets has been largely seen as limited. Whereas time-series data is volatile, geospatial data is often static. The location of an address, postcode or town, for example, doesn’t really change, making it hard to understand how its value may increase or decrease. However, space and time have a habit of crossing paths and while geospatial data analyses are relatively new techniques, financial analysts are becoming more aware of their potential.

The 'Map Go' function on the Bloomberg Terminal information service is one example of how space can be introduced as an alternative dimension of data for decision making. Adding insights about space to traditional metrics like time makes it possible to conduct new levels of research, risk management and strategic investment. Mapping a static dataset like the location of a building to a more volatile dataset like a weather system makes the geospatial data dynamic. Analysts can now correlate how the static asset or location could be impacted by anything from a nearby storm to a spike in Covid-19 cases.

Taking the example of weather, there are many reasons why geospatial analysis is becoming increasingly relevant in the world’s finance markets. Extreme weather events have become more frequent, especially in areas of high population density like the southern coast of the United States. Even in a temperate zone like the UK, the effects are plain to see. The Royal Meteorological Society’s sixth 'State of the UK Climate' report, published in July 2020, shows that 2019 was a record-breaking year for winter and summer temperature extremes. Data like this is becoming more readily available from public sources and we now have the computing power to handle such large and diverse datasets in real time.

A combination of data and technology can help draw up compelling investment-trading signals by predicting how a weather variable – like a storm with the potential to cause flooding or structural damage – might affect a factory in its path. This type of analysis can have a significant bearing on both short-term risk management and long-term seasonal effects, impacting anything from insurance premiums to real-estate values.

While different in terms of its impact, weather mapping is similar to monitoring the spread of a virus. Bloomberg started tracking Covid-19 on 29 January this year when there were 7,000 cases globally - almost all within China. The Bloomberg Terminal’s 'Map Virus Go' function reports cases as they are recorded, which allows analysts to look at how a situation has formed and therefore how it may continue to spread based on all the available data.

Using geospatial data and tools related to Covid-19, researchers can view regional coronavirus case counts compared with companies operating in this area. This means that an analyst could, for example, view a retail store in terms of its relation to the possibility of Covid-19 restrictions being tightened in its surrounding neighbourhood. This type of insight can influence decisions being made by investors, as well as supply chain managers.

Geospatial data and mapping tools add the ability to analyse spatial data in terms of its relationship with time-series data. The implications are far-reaching for those examining the impact of events - whether extreme weather or the spread of virus or disease - on businesses, industries and public services.

Bobby Shackelton is head of geospatial and Guido Fioravantti is a geospatial engineer with Bloomberg

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