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Tail Dependence - ETH - Entrepreneurial Risks - ETH Zürich

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and L(y), assumed to be constant for y > k, is estimated by:<br />

ˆL(y) = k<br />

N<br />

· (Yk,N) ˆν<br />

(3.10)<br />

with Y1,N ≥ Y2,N ≥ · · · ≥ YN,N denoting ordered statistics of the sample containing N<br />

independent and identically distributed realizations of the market return vector Y and<br />

k denoting the number of the threshold value representing the least extreme value still<br />

counted to the tail of the distribution.<br />

Ledford and Tawn [12] (1996) characterized the joint tail behavior by constant η<br />

denoting the coefficient of tail dependence and slowly varying function L(s) and established<br />

that under weak conditions:<br />

Pr(S > s, T > s) ∼ L(s) · s −1/η<br />

with 0 < η ≤ 1. It follows from the representations in [15] (1999) that<br />

as s → ∞ (3.11)<br />

χ = 2η − 1<br />

⎧<br />

⎨ c if χ = 1 and L(s) → c > 0 as s → ∞<br />

(3.12)<br />

χ = 0 if χ = 1 and L(s) → 0 as s → ∞<br />

⎩<br />

0 if χ < 1<br />

(3.13)<br />

χ = 1 corresponds to η = 1 and yields χ = lims→∞ L(s). Thus the estimation of η<br />

and lims→∞ L(s) provides the basis for the estimation of χ and χ. According to the<br />

modeling assumption for the bivariate case, for Z = min(S, T):<br />

Pr(Z > z) = Pr (min(S, T) > z)<br />

= Pr(S > z, T > z) (3.14)<br />

= L(z) · z −1/η<br />

for z > Zk,N<br />

for some high threshold number k. As η is the tail index of the univariate variable Z, it<br />

can be estimated by equation (3.9) using Hill’s estimator restricted to the interval (0, 1]<br />

and lims→∞ L(s) can be estimated using equation (3.10). The following estimators are<br />

based on the assumption of independent observations on Z. χ was estimated to:<br />

ˆχ = 2<br />

�<br />

k� � �<br />

Zj,N<br />

log<br />

k Zk,N<br />

j=1<br />

�<br />

− 1 (3.15)<br />

var � ˆχ � �<br />

ˆχ + 1<br />

=<br />

�2 (3.16)<br />

k<br />

The estimator of χ, only calculated if there is no significant evidence to reject χ = 1,<br />

was proposed to be:<br />

ˆχ = Zk,N · k<br />

N<br />

var(ˆχ) = Zk,N 2 k(N − k)<br />

N3 (3.17)<br />

(3.18)<br />

ˆχ is a figure that could be compared to other estimators of tail dependence coefficients,<br />

which are explained in the following sections of chapter (3) because it has the same<br />

underlying definition as provided in equation (2.33) showing the formula of upper tail<br />

dependence.<br />

14

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