FRM数量分析

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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