In complex multivariate environments, certainty does not exist.
Just as the outcome of a football match can be impacted by almost every touch of the ball on the field, other multivariate environments, such as a political election or a pandemic, can be impacted by countless factors. This makes finding a certain result a difficult task.
With certainty out of reach, the best thing to do next becomes calculating probability, a far more feasible alternative. The rise of big data and artificial intelligence (AI) has dramatically changed the ease with which this can be achieved. With a large enough data set and a well-designed methodology, computer programs can glean hundreds of thousands of data points and classify the results under certain probability bands.
Users of this technology can derive significant advantages in complex multivariate environments, especially if competitors do not have this information. For example, it’s easy to imagine how knowing that a certain market move is likely to occur gives traders an edge over more ignorant competitors. The problem: This information is not easy to obtain.
Fortunately, some entrepreneurs have made it a point to create predictive technology. Tim Hwang from FiscalNote Holdings Inc. REMARKfor example, created a company specializing in collecting data and repackaging it into actionable information.
Built on modern and popular cloud technology, FiscalNote’s Predata platform leverages Big Data and AI to predict probabilistic outcomes in highly uncertain environments, giving their users a huge advantage over their competitors.
A FiscalNote case study: Predicting the movement of COVID-19
During the onslaught of the COVID-19 pandemic, individuals who could determine the trajectory of the virus had supreme advantages over others. Knowing the likely next destination of the virus, governments, for example, could put in place appropriate fortifications, and investors could hedge or liquidate positions.
FiscalNote’s Predata platform would have achieved this goal of predictability. By measuring the finite distribution of human attention across social platforms, Predata’s patented methodology transforms anonymized web traffic metadata into quantifiable measures of attention to individual stories, topics and themes. This can then be used to predict the likelihood of events.
At one point during the pandemic, for example, the Predata platform recognized this “Global interest in the outbreak was increasingly driven by Italian and Japanese-speaking audiences.” The sudden spike in interest from Italian-speaking and Japanese demographics has led to predictions that the next COVID-19 surge will occur in these regions. “Four days after the Predata alert, Italian authorities reported a sharp increase in coronavirus infections,” says FiscalNote. Predata users received individualized alerts of this prediction before it was announced by media around the world.
FiscalNote’s Predata platform was used to make several complicated predictions, ranging from the eventuality of Iran reprisals to the American strike of Soleimini at the risk of a oil shock. With the tools to simplify complex datasets and organize them into actionable information, FiscalNote would provide its clients with access to some of the most valuable information in the market – before it hits the market.
After the midterm elections, this unique service seems more important than ever.
Find out how FiscalNote can help you prepare for future events here.
Featured photo by DeepMind on Unsplash
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