This paper examines the efficiency of prediction markets by studying the markets for catastrophe (CAT) bonds, compared to previous studies of prediction markets that used small-scale observational field data or experiments. We collect actual catastrophe loss data, match the defined trigger events of each CAT bond contract, and then employ an empirical pricing framework to obtain the excess CAT premiums in order to represent the market-based forecasts. Our results indeed show that the market-based forecasts have more significantly predictive content for future CAT losses than professional forecasts that use natural catastrophe risk models. Although the predictive information for CAT events is specialized and complex, our evidence supports that CAT bond markets are successful prediction markets that efficiently aggregate information about future CAT losses. Our results also highlight that actual CAT losses in future periods can explain the excess CAT bond spreads in the primary market and provide evidence of market efficiency when pricing CAT risk.