Last year, during the hotly-contested French presidential election, a couple of economists from Banque de France used Hypermind’s trading data to measure the risk of “Frexit” and its impact on financial markets. Their research findings have recently been published in the scholarly journal Applied Economics Letters.
Their conclusion strongly underlines the usefulness of prediction markets such as Hypermind for pricing financially-relevant political risk. It is worth reading carefully:
Two messages emerge from our results:
- First, predictive markets and crowd-based forecasting appear to produce specific political information about uncertainty and risk that (i) has strong explanatory power and (ii) is not fully aggregated by financial markets, for example through stock volatility or global risk aversion.
- Second, investors appeared worried by Frexit and reacted strongly when faced with an increase in its likelihood. This suggests that, in accordance to existing literature, uncertainty regarding a specific event weighs on investors’ behaviour, even when its likelihood is low.
Overall, we think these results suggest that the study of political uncertainty spillovers across borders is both an important and promising avenue for further research and that prediction markets will provide useful data for this endeavor.