By Dr. Ankan Pal
New Delhi [India], July 22 (ANI): In a world driven by data, opinion trading, globally known as information markets, have emerged as a powerful mechanism for alleviating the accuracy of forecasting in multiple fields including economics, policy, sports, and politics. These markets allow participants to trade contracts based on the likelihood of future events and provide a mechanism of price discovery which reflects the crowd’s aggregated wisdom, often proving to be more accurate[1] than surveys, expert opinions or traditional polls based on a small sample.
The concept isn’t new – humans have long tracked markets for forecasting and understanding the sentiment and polarity.
The fascinating history of prediction markets dates back to the 15th century. It has evolved from newspaper-reported election assessments to academic experiments like the Iowa Electronic Markets, and eventually to regulated platforms like Kalshi in the U.S. Today, this 500-year journey enters its most transformative phase in India, where homegrown platforms like Probo, MPL Opinio, and others are reimagining information markets for the world’s largest democracy – blending wisdom-of-crowds principles with cutting-edge digital infrastructure and India’s unique analytical culture.
From Predicting the Next Pope to Forecasting Elections.
The history of prediction markets illustrates how humans have long used market mechanisms to aggregate dispersed knowledge. The story begins in 1503, when participants in Rome engaged in informal exchanges about who would become the next Pope[2]. This early example captures the essence of prediction markets – people investing in their forecasts, creating a dynamic and probabilistic system reflecting collective expectations.
By the 19th century, political forecasting through market mechanisms had become so sophisticated that major newspapers like The New York Times regularly forecasted based on election contracts. These informal exchanges often aggregated the dispersed knowledge with near-accurate forecasts. The trend continued into the 20th century, with economist Friedrich Hayek famously arguing in 1945 that markets excel at aggregating scattered knowledge into actionable intelligence.
The Digital Revolution in Forecasting
The late 1980s marked a turning point when the Iowa Electronic Markets (IEM) was launched as an academic experiment. This small, regulated platform allowed people to trade contracts on U.S. election outcomes. Time and again, it outperformed traditional polls, proving that incentivized crowd wisdom could beat conventional forecasting methods. Corporate America took notice. In the 1990s, Hewlett-Packard ran internal prediction exchanges where employees traded contracts on product sales. Around the same time, USA’s defence research organization DARPA, which was instrumental in the development of the Internet, explored market-based forecasting tools to anticipate surprises and predict future events relevant to national security.
The potential of prediction markets gained further validation in 2011 when U.S. intelligence agencies, including the CIA, partnered with researchers to test them through the ‘Good Judgment Project’. The surprising result? Ordinary people pooling their knowledge actually predicted world events better than government experts. Around the same time, a famous research paper, The Promise of Prediction Markets, showed how these markets could turn scattered information into useful forecasts – proving their value for businesses and governments alike.
Silicon Valley’s Strategic Tool
Tech giants soon joined the movement. Google operated two internal prediction platforms–first “Prophit” (2005-2011), and later “Gleangen” (2020), which outperformed external forecasting systems. These exchanges helped Google anticipate product delays, hiring needs, and even pandemic-related disruptions with precision. Even Facebook (now Meta) got in the game, releasing its Prophet forecasting tool to show how AI could turbocharge predictions.
Today, prediction markets are going mainstream. Kalshi (regulated by US CFTC) has now achieved a $2 billion valuation with backing from marquee investors like Sequoia Capital. It has also secured strategic partnerships with financial services providers and brokerages–including industry leader Robinhood–to enhance the legitimacy and growth of prediction markets. Then there is Polymarket, funded by PayPal and Palantir co-founder Peter Thiel, which recently teamed up with X (Twitter) to blend predictions with social media. There’s more. In a recent move, SIG – one of the biggest quantitative trading companies on the wall street – is moving towards sports trading which portrays the dynamic changes in this industry.
Why These Systems Produce Better Forecasts?
Three key principles explain their effectiveness:
First, they align incentives with accuracy- participants benefit most when their assessments prove correct, motivating analysis and research.
Second, they synthesize diverse perspectives, balancing out individual biases through the wisdom of crowd mechanism. The resulting aggregated prices reflect hundreds or thousands of informed viewpoints continuously adjusting to new information.
Third, they adapt dynamically, unlike static surveys or expert opinions. During major events like the COVID-19 pandemic, these systems rapidly reflected the emerging information while traditional models needed more time to capture the same.
India’s Moment to Lead the Global Information Markets Revolution
As prediction markets rewrite global rules–from Kalshi’s CFTC approval to Polymarket’s X integration–India faces a stark choice: precede or follow. We have seen this story before in semiconductors, quantum tech, and social media – the template is familiar. But here, with our more than 950 million internet users, fantasy sports scaling playbook, and homegrown players like Probo and MPL Opinio already punching above their weight, we hold a winning hand. This is India’s chance to usher the ‘Gyaan yug’–an era where collective intelligence meets democratic participation–while establishing global standards.
The blueprint is clear: Smart regulation + digital public infrastructure + information markets = data and forecasting supremacy. This is not just another asset class, but the convergence of finance, tech, and mass wisdom. Others are writing the rules as we speak. Will India regulate, innovate and claim its pre-eminence–or remain an observer? The next move is ours. (ANI)
Disclaimer: Dr. Ankan Pal is currently serving as an Assistant Professor at BITS Pilani. With a PhD in Mathematics, one of his interests is in the utility of information markets. He was part of a recent data intensive study, conducted in collaboration with IIT Delhi, which quantifies the predominance of skill components in Prediction Markets. The views expressed in this article are his own.
Disclaimer: This story is auto-generated from a syndicated feed of ANI; only the image & headline may have been reworked by News Services Division of World News Network Inc Ltd and Palghar News and Pune News and World News
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