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Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Optional reinsurance with ruin probability target
Arthur Charpentier
http ://blogperso.univ-rennes1.fr/arthur.charpentier/
1
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Ruin, solvency and reinsurance
“reinsurance plays an important role in reducing the risk in an insurance
portfolio.”
Goovaerts & Vyncke (2004). Reinsurance Forms in Encyclopedia of Actuarial
Science.
“reinsurance is able to offer additional underwriting capacity for cedants, but also
to reduce the probability of a direct insurer’s ruin .”
Engelmann & Kipp (1995). Reinsurance. in Encyclopaedia of Financial
Engineering and Risk Management.
2
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional Reinsurance (Quota-Share)
• claim loss X : αX paid by the cedant, (1 − α)X paid by the reinsurer,
• premium P : αP kept by the cedant, (1 − α)P transfered to the reinsurer,
Nonproportional Reinsurance (Excess-of-Loss)
• claim loss X : min{X, u} paid by the cedant, max{0, X − u} paid by the
reinsurer,
• premium P : Pu kept by the cedant, P − Pu transfered to the reinsurer,
3
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional versus nonproportional reinsurance
claim 1 claim 2 claim 3 claim 4 claim 5
reinsurer
cedent
02468101214
Proportional reinsurance (QS)
claim 1 claim 2 claim 3 claim 4 claim 5
reinsurer
cedent
02468101214
Nonproportional reinsurance (XL)
Fig. 1 – Reinsurance mechanism for claims indemnity, proportional versus non-
proportional treaties.
4
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Mathematical framework
Classical Cram´er-Lundberg framework :
• claims arrival is driven by an homogeneous Poisson process, Nt ∼ P(λt),
• durations between consecutive arrivals Ti+1 − Ti are independent E(λ),
• claims size X1, · · · , Xn, · · · are i.i.d. non-negative random variables,
independent of claims arrival.
Let Yt =
Nt
i=1
Xi denote the aggregate amount of claims during period [0, t].
5
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Premium
The pure premium required over period [0, t] is
πt = E(Yt) = E(Nt)E(X) = λE(X)
π
t.
Note that more general premiums can be considered, e.g.
• safety loading proportional to the pure premium, πt = [1 + λ] · E(Yt),
• safety loading proportional to the variance, πt = E(Yt) + λ · V ar(Yt),
•
safety loading proportional to the standard deviation, πt = E(Yt) + λ · V ar(Yt),
• entropic premium (exponential expected utility) πt =
1
α
log E(eαYt
) ,
• Esscher premium πt =
E(X · eαYt
)
E(eαYt )
,
• Wang distorted premium πt =
∞
0
Φ Φ−1
(P(Yt > x)) + λ dx,
6
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
A classical solvency problem
Given a ruin probability target, e.g. 0.1%, on a give, time horizon T, find capital
u such that,
ψ(T, u) = 1 − P(u + πt ≥ Yt, ∀t ∈ [0, T])
= 1 − P(St ≥ 0∀t ∈ [0, T])
= P(inf{St} < 0) = 0.1%,
where St = u + πt − Yt denotes the insurance company surplus.
7
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
A classical solvency problem
After reinsurance, the net surplus is then
S
(θ)
t = u + π(θ)
t −
Nt
i=1
X
(θ)
i ,
where π(θ)
= E
N1
i=1
X
(θ)
i and



X
(θ)
i = θXi, θ ∈ [0, 1], for quota share treaties,
X
(θ)
i = min{θ, Xi}, θ > 0, for excess-of-loss treaties.
8
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Classical answers : using upper bounds
Instead of targeting a ruin probability level, Centeno (1986) and Chapter 9 in
Dickson (2005) target an upper bound of the ruin probability.
In the case of light tailed claims, let γ denote the “adjustment coefficient”,
defined as the unique positive root of
λ + πγ = λMX(γ), where MX(t) = E(exp(tX)).
The Lundberg inequality states that
0 ≤ ψ(T, u) ≤ ψ(∞, u) ≤ exp[−γu] = ψCL(u).
Gerber (1976) proposed an improvement in the case of finite horizon (T < ∞).
9
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Classical answers : using approximations u → ∞
de Vylder (1996) proposed the following approximation, assuming that
E(|X|3
) < ∞,
ψdV (u) ∼
1
1 + θ
exp −
β θ µ
1 + θ
quand u → ∞
where
θ =
2µm3
3m2
2
θ et β =
3m2
m3
.
Beekman (1969) considered
ψB (u)
1
1 + θ
[1 − Γ (u)] quand u → ∞
where Γ is the c.d.f. of the Γ(α, β) distribution
α =
1
1 + θ
1 +
4µm3
3m2
2
− 1 θ et β = 2µθ m2 +
4µm3
3m2
2
− m2 θ
−1
10
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Classical answers : using approximations u → ∞
R´enyi - see Grandell (2000) - proposed an exponential approximation of the
convoluted distribution function
ψR (u) ∼
1
1 + θ
exp −
2µθu
m2 (1 + θ)
quand u → ∞
In the case of subexponential claims
ψSE (u) ∼
1
θµ
µ −
u
0
F (x) dx
11
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Classical answers : using approximations u → ∞
CL dV B R SE
Exponential yes yes yes yes no
Gamma yes yes yes yes no
Weibull no yes yes yes β ∈]0, 1[
Lognormal no yes yes yes yes
Pareto no α > 3 α > 3 α > 2 yes
Burr no αγ > 3 αγ > 3 αγ > 2 yes
12
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
With proportional reinsurance, if 1 − α is the ceding ratio,
S
(α)
t = u + απt −
Nt
i=1
αXi = (1 − α)u + αSt
Reinsurance can always decrease ruin probability.
Assuming that there was ruin (without reinsurance) before time T, if the insurance had
ceded a proportion 1 − α∗
of its business, where
α∗
=
u
u − inf{St, t ∈ [0, T]}
,
there would have been no ruin (at least on the period [0, T]).
α∗
=
u
u − min{St, t ∈ [0, T]}
1(min{St, t ∈ [0, T]} < 0) + 1(min{St, t ∈ [0, T]} ≥ 0),
then
ψ(T, u, α) = ψ(T, u) · P(α∗
≤ α).
13
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
q
q
0.0 0.2 0.4 0.6 0.8 1.0
−4−2024
Time (one year)
Impact of proportional reinsurance in case of ruin
Fig. 2 – Proportional reinsurance used to decrease ruin probability, the plain line is
the brut surplus, and the dotted line the cedant surplus with a reinsurance treaty.
14
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
In that case, the algorithm to plot the ruin probability as a function of the reinsurance
share is simply the following
RUIN <- 0; ALPHA <- NA
for(i in 1:Nb.Simul){
T <- rexp(N,lambda); T <- T[cumsum(T)<1]; n <- length(T)
X <- r.claims(n); S <- u+premium*cumsum(T)-cumsum(X)
if(min(S)<0) { RUIN <- RUIN +1
ALPHA <- c(ALPHA,u/(u-min(S))) }
}
rate <- seq(0,1,by=.01); proportion <- rep(NA,length(rate))
for(i in 1:length(rate)){
proportion[i]=sum(ALPHA<rate[i])/length(ALPHA)
}
plot(rate,proportion*RUIN/Nb.Simul)
15
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
0.0 0.2 0.4 0.6 0.8 1.0
0123456
Cedent's quota share
Ruinprobability(in%)
Pareto claims
Exponential claims
Fig. 3 – Ruin probability as a function of the cedant’s share.
16
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
0.0 0.2 0.4 0.6 0.8 1.0
020406080100
rate
Ruinprobability(w.r.t.nonproportionalcase,in%)
1.05 (tail index of Pareto individual claims)
1.25
1.75
3
Fig. 4 – Ruin probability as a function of the cedant’s share.
17
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Nonproportional reinsurance (QS)
With nonproportional reinsurance, if d ≥ 0 is the priority of the reinsurance contract,
the surplus process for the company is
S
(d)
t = u + π(d)
t −
Nt
i=1
min{Xi, d} where π(d)
= E(S
(d)
1 ) = E(N1) · E(min{Xi, d}).
Here the problem is that it is possible to have a lot of small claims (smaller than d), and
to have ruin with the reinsurance cover (since p(d)
< p and min{Xi, d} = Xi for all i if
claims are no very large), while there was no ruin without the reinsurance cover (see
Figure 5).
18
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
q
q
0.0 0.2 0.4 0.6 0.8 1.0
−2−1012345
Time (one year)
Impact of nonproportional reinsurance in case of nonruin
Fig. 5 – Case where nonproportional reinsurance can cause ruin, the plain line is
the brut surplus, and the dotted line the cedant surplus with a reinsurance treaty.
19
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
Proportional reinsurance (QS)
0 5 10 15 20
01234567
Deductible of the reinsurance treaty
Ruinprobability(in%)
Fig. 6 – Monte Carlo computation of ruin probabilities, where n = 10, 000 trajec-
tories are generated for each deductible, with a 95% confidence interval.
20
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
R´ef´erences
[1] Asmussen, S. (2000). Ruin Probability. World Scientific Publishing Company.
[2] Beekmann, J.A. (1969). A ruin function approximation. Transactions of the Society
of Actuaries,21, 41-48.
[3] B¨uhlmann, H. (1970). Mathematical Methods in Risk Theory. Springer-Verlag.
[4] Burnecki, K. Mista, P. & Weron, A. (2005). Ruin Probabilities in Finite and
Infinite Time. in Statistical Tools for Finance and Insurance, C´ızek,P., H¨ardle, W.
& Weron, R. Eds., 341-380. Springer Verlag.
[5] Centeno, L. (1986). Measuring the Effects of Reinsurance by the Adjustment
Coefficient. Insurance : Mathematics and Economics 5, 169-182.
[6] Dickson, D.C.M. & Waters, H.R. (1996). Reinsurance and ruin. Insurance :
Mathematics and Economics, 19, 1, 61-80.
[7] Dickson, D.C.M. (2005). Reinsurance risk and ruin. Cambridge University Press.
21
Arthur CHARPENTIER - Optimal reinsurance with ruin probability target
[8] Engelmann, B. & Kipp, S. (1995). Reinsurance. in Peter Moles (ed.) :
Encyclopaedia of Financial Engineering and Risk Management, New York &
London : Routledge.
[9] Gerber, H.U. (1979). An Introduction to Mathematical Risk Theory. Huebner.
[10] Grandell, J. (1991). Aspects of Risk Theory. Springer Verlag.
[11] Goovaerts, M. & Vyncke, D. (2004). Reinsurance forms. in Encyclopedia of
Actuarial Science, Wiley, Vol. III , 1403-1404.
[12] Kravych, Y. (2001). On existence of insurer’s optimal excess of loss reinsurance
strategy. Proceedings of 32nd ASTIN Colloquium.
[13] de Longueville, P. (1995). Optimal reinsurance from the point of view of the excess
of loss reinsurer under the finite-time ruin criterion.
[14] de Vylder, F.E. (1996). Advanced Risk Theory. A Self-Contained Introduction.
Editions de l’Universit de Bruxelles and Swiss Association of Actuaries.
22

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Slides lyon-anr

  • 1. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Optional reinsurance with ruin probability target Arthur Charpentier http ://blogperso.univ-rennes1.fr/arthur.charpentier/ 1
  • 2. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Ruin, solvency and reinsurance “reinsurance plays an important role in reducing the risk in an insurance portfolio.” Goovaerts & Vyncke (2004). Reinsurance Forms in Encyclopedia of Actuarial Science. “reinsurance is able to offer additional underwriting capacity for cedants, but also to reduce the probability of a direct insurer’s ruin .” Engelmann & Kipp (1995). Reinsurance. in Encyclopaedia of Financial Engineering and Risk Management. 2
  • 3. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional Reinsurance (Quota-Share) • claim loss X : αX paid by the cedant, (1 − α)X paid by the reinsurer, • premium P : αP kept by the cedant, (1 − α)P transfered to the reinsurer, Nonproportional Reinsurance (Excess-of-Loss) • claim loss X : min{X, u} paid by the cedant, max{0, X − u} paid by the reinsurer, • premium P : Pu kept by the cedant, P − Pu transfered to the reinsurer, 3
  • 4. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional versus nonproportional reinsurance claim 1 claim 2 claim 3 claim 4 claim 5 reinsurer cedent 02468101214 Proportional reinsurance (QS) claim 1 claim 2 claim 3 claim 4 claim 5 reinsurer cedent 02468101214 Nonproportional reinsurance (XL) Fig. 1 – Reinsurance mechanism for claims indemnity, proportional versus non- proportional treaties. 4
  • 5. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Mathematical framework Classical Cram´er-Lundberg framework : • claims arrival is driven by an homogeneous Poisson process, Nt ∼ P(λt), • durations between consecutive arrivals Ti+1 − Ti are independent E(λ), • claims size X1, · · · , Xn, · · · are i.i.d. non-negative random variables, independent of claims arrival. Let Yt = Nt i=1 Xi denote the aggregate amount of claims during period [0, t]. 5
  • 6. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Premium The pure premium required over period [0, t] is πt = E(Yt) = E(Nt)E(X) = λE(X) π t. Note that more general premiums can be considered, e.g. • safety loading proportional to the pure premium, πt = [1 + λ] · E(Yt), • safety loading proportional to the variance, πt = E(Yt) + λ · V ar(Yt), • safety loading proportional to the standard deviation, πt = E(Yt) + λ · V ar(Yt), • entropic premium (exponential expected utility) πt = 1 α log E(eαYt ) , • Esscher premium πt = E(X · eαYt ) E(eαYt ) , • Wang distorted premium πt = ∞ 0 Φ Φ−1 (P(Yt > x)) + λ dx, 6
  • 7. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target A classical solvency problem Given a ruin probability target, e.g. 0.1%, on a give, time horizon T, find capital u such that, ψ(T, u) = 1 − P(u + πt ≥ Yt, ∀t ∈ [0, T]) = 1 − P(St ≥ 0∀t ∈ [0, T]) = P(inf{St} < 0) = 0.1%, where St = u + πt − Yt denotes the insurance company surplus. 7
  • 8. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target A classical solvency problem After reinsurance, the net surplus is then S (θ) t = u + π(θ) t − Nt i=1 X (θ) i , where π(θ) = E N1 i=1 X (θ) i and    X (θ) i = θXi, θ ∈ [0, 1], for quota share treaties, X (θ) i = min{θ, Xi}, θ > 0, for excess-of-loss treaties. 8
  • 9. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Classical answers : using upper bounds Instead of targeting a ruin probability level, Centeno (1986) and Chapter 9 in Dickson (2005) target an upper bound of the ruin probability. In the case of light tailed claims, let γ denote the “adjustment coefficient”, defined as the unique positive root of λ + πγ = λMX(γ), where MX(t) = E(exp(tX)). The Lundberg inequality states that 0 ≤ ψ(T, u) ≤ ψ(∞, u) ≤ exp[−γu] = ψCL(u). Gerber (1976) proposed an improvement in the case of finite horizon (T < ∞). 9
  • 10. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Classical answers : using approximations u → ∞ de Vylder (1996) proposed the following approximation, assuming that E(|X|3 ) < ∞, ψdV (u) ∼ 1 1 + θ exp − β θ µ 1 + θ quand u → ∞ where θ = 2µm3 3m2 2 θ et β = 3m2 m3 . Beekman (1969) considered ψB (u) 1 1 + θ [1 − Γ (u)] quand u → ∞ where Γ is the c.d.f. of the Γ(α, β) distribution α = 1 1 + θ 1 + 4µm3 3m2 2 − 1 θ et β = 2µθ m2 + 4µm3 3m2 2 − m2 θ −1 10
  • 11. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Classical answers : using approximations u → ∞ R´enyi - see Grandell (2000) - proposed an exponential approximation of the convoluted distribution function ψR (u) ∼ 1 1 + θ exp − 2µθu m2 (1 + θ) quand u → ∞ In the case of subexponential claims ψSE (u) ∼ 1 θµ µ − u 0 F (x) dx 11
  • 12. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Classical answers : using approximations u → ∞ CL dV B R SE Exponential yes yes yes yes no Gamma yes yes yes yes no Weibull no yes yes yes β ∈]0, 1[ Lognormal no yes yes yes yes Pareto no α > 3 α > 3 α > 2 yes Burr no αγ > 3 αγ > 3 αγ > 2 yes 12
  • 13. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) With proportional reinsurance, if 1 − α is the ceding ratio, S (α) t = u + απt − Nt i=1 αXi = (1 − α)u + αSt Reinsurance can always decrease ruin probability. Assuming that there was ruin (without reinsurance) before time T, if the insurance had ceded a proportion 1 − α∗ of its business, where α∗ = u u − inf{St, t ∈ [0, T]} , there would have been no ruin (at least on the period [0, T]). α∗ = u u − min{St, t ∈ [0, T]} 1(min{St, t ∈ [0, T]} < 0) + 1(min{St, t ∈ [0, T]} ≥ 0), then ψ(T, u, α) = ψ(T, u) · P(α∗ ≤ α). 13
  • 14. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) q q 0.0 0.2 0.4 0.6 0.8 1.0 −4−2024 Time (one year) Impact of proportional reinsurance in case of ruin Fig. 2 – Proportional reinsurance used to decrease ruin probability, the plain line is the brut surplus, and the dotted line the cedant surplus with a reinsurance treaty. 14
  • 15. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) In that case, the algorithm to plot the ruin probability as a function of the reinsurance share is simply the following RUIN <- 0; ALPHA <- NA for(i in 1:Nb.Simul){ T <- rexp(N,lambda); T <- T[cumsum(T)<1]; n <- length(T) X <- r.claims(n); S <- u+premium*cumsum(T)-cumsum(X) if(min(S)<0) { RUIN <- RUIN +1 ALPHA <- c(ALPHA,u/(u-min(S))) } } rate <- seq(0,1,by=.01); proportion <- rep(NA,length(rate)) for(i in 1:length(rate)){ proportion[i]=sum(ALPHA<rate[i])/length(ALPHA) } plot(rate,proportion*RUIN/Nb.Simul) 15
  • 16. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) 0.0 0.2 0.4 0.6 0.8 1.0 0123456 Cedent's quota share Ruinprobability(in%) Pareto claims Exponential claims Fig. 3 – Ruin probability as a function of the cedant’s share. 16
  • 17. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) 0.0 0.2 0.4 0.6 0.8 1.0 020406080100 rate Ruinprobability(w.r.t.nonproportionalcase,in%) 1.05 (tail index of Pareto individual claims) 1.25 1.75 3 Fig. 4 – Ruin probability as a function of the cedant’s share. 17
  • 18. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Nonproportional reinsurance (QS) With nonproportional reinsurance, if d ≥ 0 is the priority of the reinsurance contract, the surplus process for the company is S (d) t = u + π(d) t − Nt i=1 min{Xi, d} where π(d) = E(S (d) 1 ) = E(N1) · E(min{Xi, d}). Here the problem is that it is possible to have a lot of small claims (smaller than d), and to have ruin with the reinsurance cover (since p(d) < p and min{Xi, d} = Xi for all i if claims are no very large), while there was no ruin without the reinsurance cover (see Figure 5). 18
  • 19. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) q q 0.0 0.2 0.4 0.6 0.8 1.0 −2−1012345 Time (one year) Impact of nonproportional reinsurance in case of nonruin Fig. 5 – Case where nonproportional reinsurance can cause ruin, the plain line is the brut surplus, and the dotted line the cedant surplus with a reinsurance treaty. 19
  • 20. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target Proportional reinsurance (QS) 0 5 10 15 20 01234567 Deductible of the reinsurance treaty Ruinprobability(in%) Fig. 6 – Monte Carlo computation of ruin probabilities, where n = 10, 000 trajec- tories are generated for each deductible, with a 95% confidence interval. 20
  • 21. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target R´ef´erences [1] Asmussen, S. (2000). Ruin Probability. World Scientific Publishing Company. [2] Beekmann, J.A. (1969). A ruin function approximation. Transactions of the Society of Actuaries,21, 41-48. [3] B¨uhlmann, H. (1970). Mathematical Methods in Risk Theory. Springer-Verlag. [4] Burnecki, K. Mista, P. & Weron, A. (2005). Ruin Probabilities in Finite and Infinite Time. in Statistical Tools for Finance and Insurance, C´ızek,P., H¨ardle, W. & Weron, R. Eds., 341-380. Springer Verlag. [5] Centeno, L. (1986). Measuring the Effects of Reinsurance by the Adjustment Coefficient. Insurance : Mathematics and Economics 5, 169-182. [6] Dickson, D.C.M. & Waters, H.R. (1996). Reinsurance and ruin. Insurance : Mathematics and Economics, 19, 1, 61-80. [7] Dickson, D.C.M. (2005). Reinsurance risk and ruin. Cambridge University Press. 21
  • 22. Arthur CHARPENTIER - Optimal reinsurance with ruin probability target [8] Engelmann, B. & Kipp, S. (1995). Reinsurance. in Peter Moles (ed.) : Encyclopaedia of Financial Engineering and Risk Management, New York & London : Routledge. [9] Gerber, H.U. (1979). An Introduction to Mathematical Risk Theory. Huebner. [10] Grandell, J. (1991). Aspects of Risk Theory. Springer Verlag. [11] Goovaerts, M. & Vyncke, D. (2004). Reinsurance forms. in Encyclopedia of Actuarial Science, Wiley, Vol. III , 1403-1404. [12] Kravych, Y. (2001). On existence of insurer’s optimal excess of loss reinsurance strategy. Proceedings of 32nd ASTIN Colloquium. [13] de Longueville, P. (1995). Optimal reinsurance from the point of view of the excess of loss reinsurer under the finite-time ruin criterion. [14] de Vylder, F.E. (1996). Advanced Risk Theory. A Self-Contained Introduction. Editions de l’Universit de Bruxelles and Swiss Association of Actuaries. 22