Prediction markets, also known as event derivatives or binary bets, are becoming increasingly popular among traders.
Devexperts, which develops software for capital markets firms, recently delved into how to build a prediction market.
Historically, these markets drew attention during key election cycles before fading into the background. However, with looser US regulations and a wave of innovative, easy-to-use trading platforms, event-based trading is seeing a resurgence -- prompting many to ask whether it could become the next "killer app" in FinTech, it said.
Prediction markets have existed for centuries, predating traditional securities exchanges. Early examples date back to 16th-century Italy, where citizens placed bets on papal successors, and 18th-century Britain, where wagers were made on parliamentary elections. Despite their popularity, many authorities viewed them as subversive. The digital era has transformed prediction markets. Online access has enabled broader participation and more accurate crowd-based insights.
Prediction markets are simple yet powerful. Participants buy "yes" or "no" contracts priced according to perceived probabilities, with each correct prediction returning $1 per contract. For instance, markets like Polymarket and Kalshi currently speculate on whether Federal Reserve chair Jerome Powell will remain in his post. At 20 cents per "yes" contract, traders effectively assign a 20% chance of his removal. These probabilities fluctuate with real-world events, making prediction markets highly responsive to political and economic developments.
Their appeal lies in their accuracy. Studies have shown that real-money prediction markets often outperform polls and expert forecasts, Devexperts explained. Having "skin in the game" motivates participants to make rational, data-driven predictions. These markets have successfully forecasted major outcomes, including Donald Trump's 2024 re-election and Joe Biden's withdrawal from the race. However, they are not immune to flaws -- large bets can distort odds, and collective biases can lead markets astray, as seen in the misjudged outcomes of Brexit and the 2016 US election.
Behind the simplicity of prediction markets lies complex financial technology. Like futures exchanges, they rely on sophisticated infrastructure such as order management systems, matching engines, and administrative interfaces. Because these platforms operate 24/7, uptime, redundancy, and system resilience are critical, it said. Providers must replicate key components, use consensus algorithms to maintain data integrity, and design modular architectures to enable seamless upgrades without downtime. The technology must also handle sudden spikes in trading volume, particularly during major news events.
Prediction markets also require flexible resolution systems and anti-front-running safeguards, especially in time-sensitive contexts like sports or elections. Latency mechanisms and high scalability ensure fair play and reliability across markets with fluctuating interest.
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