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Recent polls for the 2024 US presidential elections indicate a neck-to-neck race between Donald Trump and Kamala Harris.
Every few days, these polls update to show a front-runner, only for that lead to be overtaken by the slimmest of margins.
As I follow the election and the prediction markets for it I can’t help but notice how the Web 3.0 market is feverishly betting on who will be the next US President, with over $1.5 billion worth of bets placed.
This surge in interest surrounding prediction markets does not seem to be merely a fleeting trend, but a transformative shift in how we anticipate future events.
Web 3.0 protocols like Polymarket on Polygon, Drift on Solana and Azuro on Gnosis have gained significant traction particularly during this high-stakes US election.
Even traditional platforms, such as Interactive Broker, have recently announced forecast contracts for retail investors.
These prediction markets have become so influential that major news outlets now report their odds alongside traditional polls, signaling a shift in gauging public sentiment and forecasting outcomes.
At their core, prediction markets are platforms where users bet on future event outcomes, leveraging the ‘wisdom of the crowd’ principle.
This approach suggests that collective predictions from large, diverse groups often outperform individual expert opinions.
Participants buy shares in potential outcomes, with prices reflecting perceived probabilities.
This mechanism creates a dynamic, real-time indicator of market sentiment, capable of signaling trends before they materialize in broader contexts.
With a cumulative betting volume of over $1.5 billion on Web 3.0 prediction markets, I find myself wondering what’s drawing users to these blockchain-based prediction markets?
Is the promise of a ‘trustless environment’ truly delivering significant benefits or is Web 3.0 simply offering an alternative market overlooked by traditional systems?
I posit that both are true. Issues like data falsification and allegations of voter fraud among political commentators contribute to inaccuracies and erode trust in traditional systems.
By recording each poll, vote or bet on-chain, blockchain’s distributed ledger ensures transparency through immutable smart contracts.
This fosters trust among participants and reduces the need for centralized oversight.
Also, blockchain eliminates intermediaries often required in traditional markets, as smart contracts facilitate the distribution of transactions, record-keeping and rewards across the network.
That’s not to say Web 3.0 platforms aren’t borrowing from the traditional playbook.
While political events have historically driven spikes in prediction market activity, these platforms are now expanding their focus to sustain user engagement beyond electoral cycles.
Platforms like Polymarket are emulating their Web 2.0 counterparts such as Betting.com and Kalshi by diversifying into sectors like sports, entertainment, science and technology.
This strategic expansion allows users to speculate on a broad array of topics, from movie release dates to scientific breakthroughs, thereby broadening their appeal and utility.
However, the rise of prediction markets is not without challenges.
Regulatory uncertainties pose significant hurdles, as governments grapple with classifying these platforms within existing legal frameworks.
Past popular prediction markets like Intrade, once a leading platform, were shut down due to financial investigations and irregularities, highlighting the precarious balance between market demand and regulation.
In the financial markets, prediction markets often represent zero-sum situations a dollar won by one participant is a dollar lost by another.
Unlike traditional investments, bets in prediction markets do not create new value they merely transfer existing value between participants.
This leads to another challenge articipants typically expect quick outcomes and are highly invested in one side of the wager.
However, prediction markets often deal with longer-term horizons, and unless the event is a major national or global event, these markets may lack the community engagement and excitement commonly found in sports betting.
Moreover, while the ‘wisdom of the crowd’ has proven effective in many instances, it is not infallible.
Herd mentality can lead to distorted probabilities, and the overrepresentation of certain demographics within these platforms may skew results, undermining the diversity that fuels accurate predictions.
Despite these challenges, I’ve seen firsthand the remarkable potential of prediction markets.
During the ongoing 2024 U.S. elections, some prediction platforms adjusted their odds in real-time based on unfolding events, often outpacing traditional news outlets and polls with accuracy.
Such instances underscore their capacity to assimilate information fast and reflect it in market sentiments.
As I look ahead, I believe the success of prediction market platforms will hinge on their ability to adapt to changing user interests and global circumstances.
Enhancing predictive analytics through machine learning and AI (artificial intelligence) could significantly refine their accuracy, making them even more valuable tools for forecasting.
By aligning with emerging trends and leveraging innovative technologies, these platforms stand at the forefront of a new era in forecasting.
It’s not just about predicting outcomes it’s about shaping a more informed and responsive society.
As we embrace these advancements, I believe that prediction markets will become indispensable tools for navigating the uncertainties of tomorrow.
Ryan Sze Tho is the investment manager at aelf who leads strategic investment initiatives and oversees portfolio management for the layer-one blockchain. Previously the investment and research manager at KuCoin Labs, Ryan was pivotal in leading end-to-end investment deals and negotiations. He holds a Master of Science in quantitative finance from Singapore Management University and a Bachelor of Commerce in accounting and finance from the University of Western Australia.
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