skininthegame

What are some examples of prediction markets getting it wrong? 
E.g. prediction markets believed Hillary would win the 2016 US presidential election. 

Trying to build a comprehensive list of examples. 

Also curious as to strong counter-examples I.e. prediction markets were right & contrary to the “professionals”

is it more correct to view an efficient prediction market as a mechanism to provide accurate probabilities for outcomes, rather than predicting binary outcomes? 

e.g. prediction markets correctly assigned Trump a <50% probability of winning the 2016 election.

dev, armchair economist & crypto tea leaves reader - 

/futarchy /network-states x.com/nicovrg_




And if so, what is the implication for conditional markets i.e. futarchy? @nicovrg

to me prediction markets have an evaluation "resolution" that reward people who were right whereas conditional market protect holders & allow them to express their desire depending of proposal result

example ->

insider have 60% of token supply & they want to drain treasury - made of liquid stablecoins that value post execution is higher than the 60% supply they own

futarchy (conditional market) fixes this! 

to pass this proposal & drain the treasury, either insiders bid with size pass market allowing holders to exit their position, either they don't and proposal won't pass

conditional markets at least as implemented right now are less about future event prediction - as its hard to entangle effect of different proposal on token value months away - and more about allowing holders to express their desire on position according to proposal passing / failing

at least that's how it view it

one token one vote and they drain the treasury, nothing the little guy can do. as soon as proposal is public the value of token collapse, who would buy this given what's about to unfold?