• We are pleased to announce that the winner of our Feedback Prize Draw for the Winter 2024-25 session and winning £150 of gift vouchers is Zhao Liang Tay. Congratulations to Zhao Liang. If you fancy winning £150 worth of gift vouchers (from a major UK store) for the Summer 2025 exam sitting for just a few minutes of your time throughout the session, please see our website at https://www.acted.co.uk/further-info.html?pat=feedback#feedback-prize for more information on how you can make sure your name is included in the draw at the end of the session.
  • Please be advised that the SP1, SP5 and SP7 X1 deadline is the 14th July and not the 17th June as first stated. Please accept out apologies for any confusion caused.

Ruin Theory

Jia Syuen

Very Active Member
Good days to those who're studying for CM2.

Want to ask your opinions for this chapter. Do we need to memorise all the formulae in this chapter or can you suggest which one should we memorise?
 
Hi Jia

You are right that this chapter is fairly formulae heavy :-(. Hopefully by the time you've practised past questions though, many of the formulae will start to embed themselves. This is what I recommend my tutorial students learn:


Definition of a Poisson process: N(t)

Definition of a compound Poisson process: S(t) = X1 + ... + XN(t) where N(t) is Poi(λt) and Xi is the amount of the ith claim. {Xi} are i.i.d.

Definition of the surplus process: U(t) = U + ct - S(t)

Definition of premium: c = (1+θ)λE[X]

Definition of the four ruin probabilities: Ψ(U), Ψ(U,t), Ψh(U), Ψh(U,t)

Know how the factors: U, t, θ, λ, μ, σ^2 affect the ultimate and finite probabilities of ruin

Be able to solve λ +cr = λMX(r) for the adjustment coefficient r

Lundberg’s inequality: Ψ(U) ≤ exp(rU)

Definition of insurer's expected profit = θλE[X]

Be able to solve λ +cnetr = λMY(r) for the adjustment coefficient in the presence of reinsurance

Definition of cnet = (1+θ)E(S) - (1+ξ)E[SR]

Definition of insurer's expected profit in presence of reinsurance = cnet - E[SI]

Derivation of formula for upper bounds on adjustment coefficient: R < 2θm1/m2 where m1 = E[X] and m2 = E[X^2]

Derivation of formula for lower bounds on adjustment coefficient: R > (1/M) ln (c/λm1) where claim amounts are continuously distributed on (0, M)

Distribution of time until the first claim for a Poisson process: T1 is Exp(λ)

Calculate probability of ruin on first claim, P(U(T1) < 0) where U(T1) = U + cT1 - X1


Hope this is a useful list

Anna
 
  • Like
Reactions: Tim
Hi Jia

You are right that this chapter is fairly formulae heavy :-(. Hopefully by the time you've practised past questions though, many of the formulae will start to embed themselves. This is what I recommend my tutorial students learn:


Definition of a Poisson process N(t)

Definition of a compound Poisson process: S(t) = X1 + ... + XN(t) where N(t) is Poi(λt) and Xi is the amount of the ith claim. {Xi} are i.i.d.

Definition of the surplus process: U(t) = U + ct - S(t)

Definition of premium: c = (1+θ)λE[X]

Definition of the four ruin probabilities: Ψ(U), Ψ(U,t), Ψh(U), Ψh(U,t)

Know how the factors: U, t, θ, λ, μ, σ^2 affect the ultimate and finite probabilities of ruin

Be able to solve λ +cr = λMX(r) for the adjustment coefficient r

Lundberg’s inequality: Ψ(U) ≤ exp(rU)

Definition of insurer's expected profit = θλE[X]

Be able to solve λ +cnetr = λMY(r) for the adjustment coefficient in the presence of reinsurance

Definition of cnet = (1+θ) λ E - (1+ξ) λ E[SR]

Definition of insurer's expected profit in presence of reinsurance = cnet - E[SI]

Derivation of formulae for upper bounds on adjustment coefficient: R < 2θm1/m2 where m1 = E[X] and m2 = E[X^2]

Derivation of formulae for lower bounds on adjustment coefficient: R > (1/M) ln (c/λm1) where claim amounts are continuously distributed on (0, M)

Distribution of time until the first claim for a Poisson process: T1 is Exp(λ)

Calculate probability of ruin on first claim, P(U(T1) < 0) where U(T1) = U + cT1 - X1


Hope this is a useful list

Anna
Thanks for your reply! It helps a lot.
 
You're welcome - sorry, couldn't get the formatting right for ages - kept putting a line through my maths! Think I've sorted it now though :)
 
Back
Top