Traces the history of prediction markets from 1419 Vatican papal elections through the Iowa Electronic Markets to the Polymarket era, arguing the sector is at an inflection point. Surveys the insider trading scandals (Musk tweets, French elections), moral hazard concerns (assassination markets), and the wave of new entrants (Robinhood, DraftKings, Crypto.com, FanDuel) that signal mainstream adoption. Concludes that prediction markets are evolving, not decaying, but need regulatory clarity and structural reform to mature.

Documents a pattern of insider trading on prediction markets, from wallets that profited $1.2 million on the timing of US strikes on Iran to trades linked to classified intelligence. Compares how Kalshi's KYC-based surveillance and Polymarket's pseudonymous blockchain create different enforcement challenges. Argues platforms should reconsider contract offerings before regulators act.

Written during the US-Israel strikes on Iran, examines whether prediction markets on armed conflicts are net informational goods or perverse incentive engines. Dissects the IDF insider trading case where soldiers traded Polymarket positions before strikes, the CFTC's regulatory stance, and the divergent approaches of Kalshi (regulated, avoids conflict markets) versus Polymarket (offshore, lists them freely). Argues the information value is real but the moral hazard is structurally underpriced, and proposes guardrails including delayed settlement and conflict-of-interest screens.

Argues that prediction markets are financial instruments, not gambling, by examining Polymarket's architecture across multiple layers: peer-to-peer order book mechanics, information aggregation through skin-in-the-game pricing, hedging use cases, and UX design that suppresses gambling patterns. Contrasts the exchange model with the house-edge casino model to argue the gambling label stems from outdated legal frameworks.

Argues that leverage solves, rather than amplifies, prediction market problems. In a 1x market, only whales can move prices because the barrier is capital, not insight; at 10x, thousands of smaller traders can collectively contest a mispricing. Addresses gap risk (binary resolution makes platform-native margin dangerous) by describing a temporal arbitrage approach where leveraged markets close before event resolution. Also proposes a vault-based yield layer where LPs earn returns from trading activity rather than directional outcome exposure.

Argues that nearly any prediction market tied to a public figure's actions, tenure, or appearances implicitly embeds assassination as a resolution path — what the authors call 'kinetic intervention.' Uses the Charlie Kirk assassination and subsequent Kalshi market voiding as the central case study. Warns that blanket void-on-death rules can backfire by incentivizing violence from losing bettors, and proposes that platforms hire geopolitical risk officers to evaluate resolution wording, monitor anomalous betting signals (BETINT), and build early-warning capacity before tragedy occurs.

Examines Clinton and Huang's research on 2024 election market accuracy, finding PredictIt at 93%, Kalshi at 78%, and Polymarket at 67%, while also documenting significant cross-platform price divergences for identical contracts near Election Day. Raises concerns about Kalshi's media partnerships with CNN and CNBC, arguing they create incentives for sensational coverage of market movements and potential manipulation of thin markets.

Examines how to distinguish wash trading from legitimate market making on Polymarket using network analysis. Wash traders exhibit homophily, trading only within their collusive group, while market makers trade indiscriminately with diverse counterparties. Describes an algorithm developed by Columbia researchers that identified a cluster of 200 wallets generating $113 million in volume with just $57.86 in aggregate losses.

Large-scale field experiment testing prediction market manipulation across 817 markets. Randomly shocked prices and tracked effects over 60 days with hourly data. Finds markets can be manipulated with effects persisting for months, though they gradually fade. Markets with more traders, higher volume, and external probability estimates prove more resistant.