Under the European Union’s Solvency II regulations, insurance firms are required to use a one-year VaR (Value at Risk) approach. This involves a one-year projection of the balance sheet and requires sufficient capital to be solvent in 99.5% of outcomes. The Solvency II Internal Model risk calibrations require annual changes in market indices/term structure/transitions for the estimation of the risk distribution for each of the Internal Model risk drivers.

Transition and default risk are typically modelled using transition matrices. To model this risk requires a model of transition matrices and how these can change from year to year. In this paper, four such models have been investigated and compared to the raw data they are calibrated to. The models investigated are:

• A bootstrapping approach – sampling from an historical data set with replacement.

• The Vašíček model was calibrated using the Belkin approach.

• The K-means model – a new non-parametric model produced using the K-means clustering algorithm.

• A two-factor model – a new parametric model, using two factors (instead of a single factor with the Vašíček) to represent each matrix.

The models are compared in several ways:

1. 1. A principal components analysis (PCA) approach that compares how closely the models move compared to the raw data.

2. 2. A backtesting approach that compares how each model’s extreme percentile compares to regulatory backtesting requirements.

3. 3. A commentary on the amount of expert judgement in each model.

4. 4. Model simplicity and breadth of uses are also commented on.

We propose an easy to implement yield curve extrapolation method to determine long-term interest rates suitable for regulatory valuation. We empirically evaluate this approach for the German nominal bond market, by estimating the model on bonds with maturities up to 20 years and assessing the out-of-sample performance for bonds with maturities beyond 20 years. Even though observed long-term yields are somewhat lower than the predicted yields, the method performs quite well empirically given its simplicity. We perform a case study on pension fund liability valuation and show that our proposed method would have a substantial impact on liability values.

This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions – buy-outs, buy-ins and longevity insurance – have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions – longevity-spread bonds, longevity swaps, q-forwards and tail-risk protection – have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customised solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g. determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognise that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined – such as longevity-linked securities and reinsurance sidecars.

We model in a dynamic way an insider's private information flow which is successively augmented by a family of initial enlargement of filtrations. According to the a priori available information, we propose several density hypotheses which are presented in hierarchical order from the weakest to the strongest. We compare these hypotheses, in particular, with Jacod's one, and deduce conditional expectations under each of them by providing consistent expressions with respect to the common reference filtration. Finally, this framework is applied to a default model with insider information on the default threshold and some numerical illustrations are performed.

In the paper we present a novel construction of Marshall–Olkin (MO) multivariate exponential distributions of failure times as distributions of the first-passage times of the coordinates of multidimensional Lévy subordinator processes above independent unit-mean exponential random variables. A time-inhomogeneous version is also given that replaces Lévy subordinators with additive subordinators. An attractive feature of MO distributions for applications, such as to portfolio credit risk, is its singular component that yields positive probabilities of simultaneous defaults of multiple obligors, capturing the default clustering phenomenon. The drawback of the original MO fatal shock construction of MO distributions is that it requires one to simulate 2n-1 independent exponential random variables. In practice, the dimensionality is typically on the order of hundreds or thousands of obligors in a large credit portfolio, rendering the MO fatal shock construction infeasible to simulate. The subordinator construction reduces the problem of simulating a rich subclass of MO distributions to simulating an n-dimensional subordinator. When one works with the class of subordinators constructed from independent one-dimensional subordinators with known transition distributions, such as gamma and inverse Gaussian, or their Sato versions in the additive case, the simulation effort is linear in n. To illustrate, we present a simulation of 100,000 samples of a credit portfolio with 1,000 obligors that takes less than 18 seconds on a PC.

This paper evaluates vulnerable American put options under jump–diffusion assumptions on the underlying asset and the assets of the counterparty. Sudden shocks on the asset prices are described as a compound Poisson process. Analytical pricing formulae of vulnerable European put options and vulnerable twice-exercisable European put options are derived. Employing the two-point Geske and Johnson method, we derive an approximate analytical pricing formula of vulnerable American put options under jump–diffusions. Numerical simulations are performed for investigating the impacts of jumps and default risk on option prices.

Affine processes possess the property that expectations of exponential affine transformations are given by a set of Riccati differential equations, which is the main feature of this popular class of processes. In this paper we generalise these results for expectations of more general transformations. This is of interest in, e.g. doubly stochastic Markov models, in particular in life insurance. When using affine processes for modelling the transition rates and interest rate, the results presented allow for easy calculation of transition probabilities and expected present values.

The nature of credit risk assessment and basis of loan approval decisions of the Farm Service Agency are analyzed in the aftermath of the black farmers' 1997 class action suit against the U.S. Department of Agriculture. This study did not uncover convincing evidence of racial discrimination against nonwhite borrowers under a binomial logistic framework based on the probability of a loan application's approval. Moreover, the collective use of more stringent and objective credit-scoring measures usually employed by commercial lenders is less evident in the Farm Service Agency's evaluation of loan applications.

Housing finance and, specifically, the subprime private label securitisation market in the US, was at the epicentre of the global financial crisis. Excessive debt expansion in the run-up to the crisis resulted in credit risk, under-identified and mispriced ex ante, and in systemic risk. This paper considers the role of financial innovation in debt markets and the changing market structure of securitisation in the evolution of the US housing price bubble. New financing vehicles contributed to growing risk, but the more salient factor was the change in the structure of securitisation, which led to unsustainable levels of debt.

A rating trigger is a particular type of debt covenant that mandates the borrower to maintain its own credit rating above a certain rating threshold, requiring, in the event of a rating downgrade, the adoption of specific enforceable actions aimed at securing the lender claims from the borrower's higher risk level. Rating triggers lower the cost of borrowing capital, but when activated, they exacerbate the borrower's need for liquidity just at the moment when its credit risk is higher, making the borrower's default more likely to occur. Despite the potential threat posed by rating triggers on debt markets, these contractual devices remain almost unregulated both in the US and in Europe. The purpose of this paper is first to analyse the effects rating triggers can have on overall market risk and second to assess the proliferation of rating triggers among large US and non-US companies in order to establish whether these contractual devices need stricter regulation. The article is divided in two parts. Sections 2 to 5 provide an overview of the different types of triggers and analyse the rationale behind their use in terms of advantages and disadvantages for both issuers and investors. In sections 6 to 9, I perform an empirical analysis by assessing the rating triggers that have been used by Dow Jones Industrial Average Index companies. I then examine the correlation between the use of rating triggers and the companies' risk profiles by measuring their credit ratings and their Altman's Z-Scores in order to find out whether triggers are mostly used by risky companies, capable of being impaired by the triggers' activation and thus posing a threat to market stability. In section 10, I strengthen the analysis by examining whether such correlation also applies to non-US companies which use rating triggers. In section 11 conclusions are drawn suggesting the introduction by US and European regulators of a specific duty to disclose all the rating triggers that listed companies include in bond indentures and in financial contracts every year.

Risk terminology varies from organisation to organisation, and actuaries working in different organisations may use different terms to refer to the same risk, or use the same nomenclature for completely different risks. This paper sets out a classification system developed by the Risk Classification Working Party for the Profession that can be used as a common reference point for discussing risk. Actuaries will not be required to use this system, but it is hoped that common terminology will reduce the possibility of confusion in discussing risks.

In recent years there has been a trend towards market consistent valuation in those institutions for which actuaries have responsibilities. The larger United Kingdom with-profits insurance companies are now preparing realistic balance sheets, both for internal purposes and also at the request of the Financial Services Authority. International accounting standards have been moving to a fair value approach. Pension fund accounting under FRS 17 has also moved in this direction.

In this paper we examine the reasons for the adoption of market consistent valuation and discuss some of the commercial implications and corporate valuation. We consider the methods and assumptions which can be used to develop market consistent valuations of cash flows typically encountered in the liabilities of financial institutions, together with some of the problems inherent in the calibration of models used for the valuation of these cash flows. The volatility assumption is crucial to the valuation of options and guarantees, and we discuss the relationship between historical and implied volatility.

While most insurance companies initially adopted formulae to value their with-profits guarantees, several offices are now using a Monte Carlo simulation approach for their realistic balance sheets. The Monte Carlo approach enables allowance to be made for management discretion in bonus and investment policy, as well as policyholder actions. However, in many cases it is possible to develop analytical formulae for cash flows approximating those payable under insurance contracts.

The valuation formulae have implications for the hedging of embedded guarantees. The authors discuss the construction of hedges for financial risks in with-profits funds, the separate perspectives of policyholders and shareholders, possible funds in which to hold hedging instruments, limitations of capital market hedging tools and the effect of taxation on hedge effectiveness.

This paper addresses the problem of longevity risk — the risk of uncertain aggregate mortality — and discusses the ways in which life assurers, annuity providers and pension plans can manage their exposure to this risk. In particular, it focuses on how they can use mortality-linked securities and over-the-counter contracts — some existing and others still hypothetical — to manage their longevity risk exposures. It provides a detailed analysis of two such securities — the Swiss Re mortality bond issued in December 2003 and the EIB/BNP longevity bond announced in November 2004. It then looks at the universe of hypothetical mortality-linked securities — other forms of longevity bonds, swaps, futures and options — and investigates their potential uses. It also addresses implementation issues, and draws lessons from the experiences of other derivative contracts. Particular attention is paid to the issues involved with the construction and use of mortality indices, the management of the associated credit risks, and possible barriers to the development of markets for these securities. It suggests that these implementation difficulties are essentially teething problems that will be resolved over time, and so leave the way open to the development of flourishing markets in a brand new class of securities.

This paper considers the impact that the current trend towards fair valuation of assets and liabilities is likely to have on risk measurement and management practices within the financial services industry. The paper analyses the different sorts of risks faced by organisations such as asset managers, pension funds, banks and insurers, and seeks to identify how their approach to the measurement and management of these sorts of risks might change as fair valuation becomes more entrenched. It argues that what it describes as traditional ‘time series’ based risk measurement is likely to be progressively displaced over time by a greater emphasis on what the paper refers to as ‘derivative pricing’ (or ‘fair value’ or ‘market consistent’) based risk modelling. It comments on the trend towards liability driven investment. The paper focuses on ‘financial’ risks (market, credit, liquidity and, more generally, asset/liability risk) rather than ‘operational’ risks, whilst noting that the dividing line between the two can be open to interpretation. Insurance risk is seen as in some respects straddling both camps.

The Capital Asset Pricing Model arises in an economy where agents have exponential utility functions and aggregate consumption is normally distributed, and gives the prices of assets with payoffs which are jointly normal with consumption. Such assets have normal marginal distributions and have dependence with consumption characterised by a normal copula. Wang has derived a transform which extends the CAPM by allowing pricing of assets in such an economy which have non-normal marginal distributions but still are normal-copula with consumption.

Here we set out the stochastic discount factors corresponding to this version of the CAPM and to Wang’s transform, and show how to calculate stochastic discount factors and hence asset prices for assets whose dependence with consumption is non-normal. We show that the impact of dependency structure on asset prices is significant.

Dependence structures for bivariate extremal events are analyzed using particular types of copula. Weak convergence results for copulas along the lines of the Pickands-Balkema-de Haan theorem provide limiting dependence structures for bivariate tail events. A characterization of these limiting copulas is also provided by means of invariance properties. The results obtained are applied to the credit risk area, where, for intensity-based default models, stress scenario dependence structures for widely traded products such as credit default swap baskets or first-to-default contract types are proposed.