Inside the trades that predicted Trump’s next move
Offshore platforms like Polymarket operate with fewer reporting obligations and often rely on crypto wallets, making user identification significantly more difficult, reveals Vijay Valecha, chief investment officer at Century Financial
02 April, 2026
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A surge in high-precision bets on geopolitical events—particularly those linked to recent US-Iran developments—has placed prediction markets like Polymarket under intense scrutiny, with growing concerns that some trades may be informed by more than just market sentiment.
According to Business Insider, analysts and researchers have described these trades as “anomalous,” with some estimates suggesting over $140m in profits tied to potentially “informed” activity across the platform in recent years.
What makes the recent activity notable is not just the scale of the bets, but their timing. In several cases, positions were reportedly taken minutes or hours before major policy announcements, prompting comparisons with traditional insider trading behaviour.
According to Vijay Valecha, chief investment officer at Century Financial, the financial industry relies on well-established statistical benchmarks to distinguish normal market activity from potentially suspicious patterns. These include metrics such as abnormal returns, cumulative abnormal returns, and trading volume ratios.
“The financial industry relies on four core metrics… If the Abnormal Return (AR)… crosses roughly 2.5 per cent, it typically starts to raise a flag,” he explains. “Once those gains add up to more than 5 per cent, it tends to signal that the move may not just be random market noise.”
By those standards, the March 2026 trading patterns appear highly unusual. Valecha points out that “just 15 minutes before Trump’s announcement on peace talks, the volume in crude oil futures was almost 10 times the average… alongside more than $2bn in S&P 500 futures notional value.”
In prediction markets, the signals were equally striking. One trader reportedly achieved a 93 per cent success rate on Iran-related bets tied to military developments—an outcome that sits well outside normal probability expectations.
“Each signal on its own might be explainable,” Valecha notes. “But taken together, they form a pattern that sits well beyond what standard statistical market surveillance benchmarks are designed to capture.”
Trading the signal, not the event
Beyond the question of timing, a deeper shift is underway in how prediction markets operate. Increasingly, traders are not just betting on events themselves, but on the communication patterns that precede them, particularly political messaging.
Valecha highlights how platforms like Polymarket have expanded into pricing behavioural signals, including how frequently political leaders post on social media.
“Prediction markets have already crossed a new frontier,” he says. “Platforms like Polymarket now run weekly bets on how many times President Trump will post on Truth Social, treating his communication habits as a tradable asset.”
This evolution reflects a broader trend where language, tone, and timing of political communication, especially via platforms like Truth Social, are increasingly influencing market positioning.
In some cases, traders have been observed pre-positioning ahead of major announcements, using data from previous bets and communication patterns to gain an informational edge. This has effectively blurred the line between market sentiment and predictive intelligence.
“The clarity of a clear line in the sand between the President’s Truth Social account and prediction markets is fading,” Valecha adds, pointing to a Bloomberg report that Trump Media is exploring the integration of its own prediction market capabilities.
Transparency without accountability
One of the defining characteristics of platforms like Polymarket is their reliance on blockchain infrastructure, which theoretically offers full transaction transparency. However, this transparency does not necessarily translate into enforceability.
Valecha explains that while transactions are visible, the identities behind them often are not.
“Even though Polymarket runs on blockchain infrastructure, it is difficult to identify potential insider trading because the trader’s nature… is unknown,” he says. “The only way to trace ownership would be through legal proceedings or cooperation with exchanges.”
This creates a paradox: while every transaction is permanently recorded and timestamped, proving intent—particularly the use of material nonpublic information—remains extremely challenging.
“On-chain transparency is good for audit, but not for detection,” Valecha notes. “If someone is suspected of insider trading, then their transactions can be traced… but insider trading requires proving that someone acted on material nonpublic information, which on-chain data does not show.”
The speed of these markets further complicates enforcement. Unlike traditional financial systems, where settlement delays can allow regulators time to intervene, blockchain-based platforms enable near-instant execution and resolution of trades.
A regulatory grey zone
The regulatory landscape surrounding prediction markets remains fragmented, particularly when comparing platforms like Polymarket with regulated counterparts such as Kalshi.
Valecha describes the current environment as a “regulatory grey zone,” where existing insider trading laws only partially apply.
“These laws were originally made for stock markets… but prediction markets are different,” he explains. “They are based on events like elections, wars, or policy decisions which don’t fit neatly into those rules.”
On regulated platforms like Kalshi, contracts are treated as financial derivatives and fall under the oversight of the Commodity Futures Trading Commission, meaning the use of non-public information can still trigger enforcement.
However, offshore platforms like Polymarket operate with fewer reporting obligations and often rely on crypto wallets, making user identification significantly more difficult.
“Because of this, enforcement is inconsistent across countries,” Valecha says. “Prediction markets, especially offshore ones, don’t have a clear system to define or enforce [insider trading].”
Insider trading or something else?
Distinguishing between insider trading, coordinated market activity, and legitimate hedging strategies is another challenge facing regulators.
According to Valecha, the observable data across these scenarios can appear almost identical, making intent the key differentiator, yet also the hardest factor to prove.
“It is hard to distinguish between these strategies as the inherent observable data remains the same,” he explains.
He outlines three broad categories of behaviour:
- Insider trading, typically characterised by “perfect timing before major events” and consistent abnormal profits
- Coordinated “whale” activity, where large players move markets through significant positions
- Legitimate hedging, where investors offset exposure elsewhere and may not generate net profits
However, the anonymity enabled by blockchain infrastructure complicates attribution.
“Platforms like Polymarket have lower KYC requirements and allow participation via crypto wallets… making it difficult for regulators to link any activity to specific individuals,” Valecha says.
A new frontier for financial markets
The convergence of prediction markets, social media signals, and geopolitical events is creating a new category of financial activity: one that sits somewhere between derivatives trading, behavioural analytics, and speculative forecasting.
While the technology underpinning these platforms offers unprecedented transparency, the absence of unified regulation raises critical questions about market integrity and investor protection.
As Valecha suggests, the issue is not just about whether unusual trades indicate insider knowledge, but whether the current system is equipped to answer that question at all.
The growing controversy has now pushed prediction markets into a regulatory spotlight. Both Polymarket and Kalshi have moved to tighten insider trading rules, introduce new surveillance measures, and restrict participation from individuals who could influence outcomes. These steps come amid mounting pressure from regulators and lawmakers, with enforcement bodies signalling that insider trading in prediction markets will be actively pursued and scrutinised more aggressively going forward, AP News stated.
For now, prediction markets remain a powerful but imperfect tool, offering real-time insights into collective expectations, while simultaneously exposing the limits of existing financial oversight frameworks.
