After reading this analysis on the risks of market manipulation in prediction markets, I have some complex thoughts.

The core logic is clear: in the AI era, fabricating public opinion has become easier. Prediction markets should be a supplementary signal to traditional polls, but they face the risk of being artificially inflated. However, there is an interesting paradox—those who truly want to manipulate markets to change election outcomes will find it costly and difficult to sustain. Rhode and Strumpf's research on Iowa electronic markets demonstrates this: manipulators pour money in, but other traders immediately exploit arbitrage mechanisms to pull prices back. Short-term disturbances may make headlines, but they fundamentally do not shake the underlying fundamentals.

The real risk isn't whether manipulation can succeed, but whether people believe it has succeeded. Once unexplained price fluctuations occur, the trust chain breaks. What does this mean for copy traders? It depends on who you follow. If the top traders you follow mainly rely on prediction markets as one of their information sources, then when market liquidity is low, signal quality will drop significantly—at this point, you should decisively reduce leverage or pause trading, rather than blindly follow.

From a governance perspective, three key points for regulation are worth noting: liquidity lower bounds, real-time monitoring of abnormal trades, and increased transparency. In simple terms, this is to prevent manipulators from being able to manipulate. For my copy trading strategy, this means that in the future, when selecting markets and traders, I will pay more attention to their market depth and trading volume characteristics—performing the same strategy in a high-liquidity market is much more reliable than in a low-liquidity one.

Experience proves that once this wave passes, prediction market platforms that survive will become more transparent and can provide more valuable signals.