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Expectile Value at Risk (EVaR) and conditional expectile are typical applications of expectiles in risk measurement; EVaR can be viewed as a loss measure that weights the tail under an asymmetric squared loss, possesses the good properties of a convex risk measure, and can be efficiently aggregated to the portfolio level through a small number of expectile levels.
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10/14/2026
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UnverifiedThe expected value formula is: Expected Value = (Win Rate × Average Profit) − (Loss Rate × Average Loss).66% similarUnverifiedConditional Value at Risk (CVaR) is defined as the expected value of the tail portion of the loss distribution exceeding a certain confidence level α, expressed mathematically as CVaR_α = E[L | L ≥ VaR_α], and possesses optimization properties such as convexity and subadditivity.64% similarVerifiedExpected Calibration Error (ECE) bins prediction samples by confidence level, computes the weighted average of the difference between predicted confidence and actual accuracy within each bin, and ideally approaches 0.59% similarUnverifiedEXPECT_FLOAT_EQ and EXPECT_DOUBLE_EQ perform comparisons based on ULP, tolerating a default deviation of 4 ULPs.58% similarUnverified在Elo系统中，若模型A评分为Ra、模型B评分为Rb，A获胜的期望概率为1/(1+10^((Rb-Ra)/400))58% similar
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