Ruin theory

In actuarial science and applied probability ruin theory (sometimes collective risk theory) uses mathematical models to describe an insurer's vulnerability to insolvency/ruin. In such models key quantities of interest are the probability of ruin, distribution of surplus immediately prior to ruin and deficit at time of ruin.

Classical model

A sample path of compound Poisson risk process

The theoretical foundation of ruin theory, known as the Cramer-Lundberg model (or classical compound-Poisson risk model, classical risk process or Poisson risk process) was introduced in 1903 by the Swedish actuary Filip Lundberg. Lundberg's work was republished in the 1930s by Harald Cramér.

The model describes an insurance company who experiences two opposing cash flows: incoming cash premiums and outgoing claims. Premiums arrive a constant rate c > 0 from customers and claims arrive according to a Poisson process and are independent and identically distributed non-negative random variables (they form a compound Poisson process). So for an insurer who starts with initial surplus x,

$X_{t}=x+ct-\sum _{i=1}^{N_{t}}\xi _{i}\qquad {\text{ for t }}\geq 0.$

The central object of the model is to investigate the probability that the insurer's surplus level eventually falls below zero (making the firm bankrupt). This quantity, called the probability of ultimate ruin, is defined as

$\psi (x)=\mathbb {P} ^{x}\{\tau <\infty \}$

where the time of ruin is $\scriptstyle \tau =\inf\{X(t)<0\}$ with the convention that $\scriptstyle \inf \varnothing =\infty$.

It is well known that the probability of ultimate ruin is the tail probability of a compound-geometric distribution. The exact solutions and asymptotic approximations to the probability of ruin rely largely on techniques of renewal theory.

Recent developments

Ruin theory received a substantial boost with the articles of Michael R. Powers in 1995 and Gerber and Shiu in 1998, which introduced the expected discounted penalty function, a generalization of the probability of ultimate ruin. This fundamental work was followed by a large number of papers in the ruin literature deriving related quantities in a variety of risk models.

Expected discounted penalty function

The articles of Powers and Gerber and Shiu analyzed the behavior of the insurer's surplus through the expected discounted penalty function, which is commonly referred to as Gerber-Shiu function in the ruin literature. It is arguable whether the function should have been called Powers-Gerber-Shiu function due to the contribution of Powers.

In Powers’ notation, this is defined as

$m(x)=\mathbb {E} ^{x}[e^{-\delta \tau }K_{\tau }]$,

where $\delta$ is the discounting force of interest, $K_{\tau }$ is a general penalty function reflecting the economic costs to the insurer at the time of ruin, and the expectation $\mathbb {E} ^{x}$ corresponds to the probability measure $\mathbb {P} ^{x}$. The function is called expected discounted cost of insolvency in Powers.

In Gerber and Shiu’s notation, it is given as

$m(x)=\mathbb {E} ^{x}[e^{-\delta \tau }w(X_{\tau -},X_{\tau })\mathbb {I} (\tau <\infty )]$,

where $\delta$ is the discounting force of interest and $w(X_{\tau -},X_{\tau })$ is a penalty function capturing the economic costs to the insurer at the time of ruin (assumed to depend on the surplus prior to ruin $X_{\tau -}$ and the deficit at ruin $X_{\tau }$), and the expectation $\mathbb {E} ^{x}$ corresponds to the probability measure $\mathbb {P} ^{x}$. Here the indicator function $\mathbb {I} (\tau <\infty )$ emphasizes that the penalty is exercised only when ruin occurs.

It is quite intuitive to interpret the expected discounted penalty function. Since the function measures the actuarial present value of the penalty that occurs at $\tau$, the penalty function is multiplied by the discounting factor $e^{-\delta \tau }$, and then averaged over the probability distribution of the waiting time to $\tau$. While Gerber and Shiu applied this function to the classical compound-Poisson model, Powers argued that an insurer’s surplus is better modeled by a family of diffusion processes.

There are a great variety of ruin-related quantities that fall into the category of the expected discounted penalty function.

Special case	Mathematical representation	Choice of penalty function
Probability of ultimate ruin	$\mathbb {P} ^{x}\{\tau <\infty \}$	$\delta =0,w(x_{1},x_{2})=1$
Joint (defective) distribution of surplus and deficit	$\mathbb {P} ^{x}\{X_{\tau -}<x,X_{\tau }<y\}$	$\delta =0,w(x_{1},x_{2})=\mathbb {I} (x_{1}<x,x_{2}<y)$
Defective distribution of claim causing ruin	$\mathbb {P} ^{x}\{X_{\tau -}-X_{\tau }<z\}$	$\delta =0,w(x_{1},x_{2})=\mathbb {I} (x_{1}+x_{2}<z)$
Trivariate Laplace transform of time, surplus and deficit	$\mathbb {E} ^{x}[e^{-\delta \tau -sX_{\tau -}-zX_{\tau }}]$	$w(x_{1},x_{2})=e^{-sx_{1}-zx_{2}}$
Joint moments of surplus and deficit	$\mathbb {E} ^{x}[X_{\tau -}^{j}X_{\tau }^{k}]$	$\delta =0,w(x_{1},x_{2})=x_{1}^{j}x_{2}^{k}$

Other finance-related quantities belonging to the class of the expected discounted penalty function include the perpetual American put option, the contingent claim at optimal exercise time, and more.

Recent developments

• Sparre-Andersen risk model
• Compound-Poisson risk model with constant interest
• Compound-Poisson risk model with stochastic interest
• Brownian-motion risk model
• General diffusion-process model
• Markov-modulated risk model
• Accident Probability Factor(APF) Calculator - Risk analysis model (@SBH)

See also

• Poisson process
• Continuous-time Markov process
• Stochastic processes
• Queueing theory

Bibliography

• Gerber, H.U. (1979). An Introduction to Mathematical Risk Theory. Philadelphia: S.S. Heubner Foundation Monograph Series 8.

• Asmussen S. (2000). Ruin Probabilities. Singapore: World Scientific Publishing Co.