Abstract: This article compares three kinds of quantile-based risk measures: VaR, ES and a new proposed coherent risk measure called iso-entropic risk measure. The main factors to be compared are convexity, the volume of information which is used to measure the risk, relationship between these risk measures and stochastic dominances. It is pointed that though ES holds convexity, it only utilizes local information as VaR and is consistent with stochastic dominances lowers than second-order. However, iso-entropic risk measure utilizes the whole information to measure the risk, it is not a 0-1 risk measure and it is consistent with stochastic dominances of almost all the orders. So, it is most powerful for discrimination of risk. Simulation cases demonstrate this.