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FRM数量分析

FRM数量分析

作者: Agoni_1f59 | 来源:发表于2020-10-09 23:17 被阅读0次

    1. The Power Law幂定律

    高峰肥尾(eg:t分布)

    V:the value of variable

    P(V>X)= K * X^(-α)

    (K,α > 0且为常数)

    X↑  P↓

    2. Correlation and Covariance:

    Covn =  E(xnyn)-  E(xn)E(yn)= E(xnyn)

    E(xn)=E(yn)=0

    rou(linear) = Cov(xn,yn)/ 6xn * 6yn

    3. Update Covariance:

    ①EWMA:

    Covn = 入Cov n-1 +(1-入)xn-1 yn-1

    ②GARCH(1,1):

    Covn = YCovL + α xn-1 yn-1 + βCov n-1

    4. Alternative measures of correlation:

    即可衡量线性,也可衡量非线性:

    Spearman’s rank correlation 和 Kendal’s tao

    rou between -1 and 1

    returns independent:rou = 0

    relationship increase:rou > 0

    relationship decrease:rou < 0

    ①Spearman’s rank correlation:

    ordinal

    nonparametric approach

    没有 linear correlation estimator有效

    可作为additional robustness check

    性质:

    ①不受outliers值影响

    ②X,Y单调性不变,rou值不变

    ②Kendall’s tao:

    ordinal

    nonparametric approach

    性质:

    ①不受outliers值影响

    ②X,Y单调性不变,tao值不变

    正序对Concordant:Xi>Xj,Yi>Yj 或者

    Xi<Xj,Yi<Yj

    异序对Discordant:Xi>Xj,Yi<Yj 或者

    Xi<Xj,Yi>Yj

    既不是正序对,也不是异序对:Xi=Xj,Yi=Yj

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