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A family succession is different from all other exit options in so far as the emphasis is often not on maximising the owner’s exit price, but rather on ensuring that the business continues successfully under the ownership of the successor. Consequently, the tailoring (or grooming) is concentrated on the successor, rather than on the business. This alters the perspective of the business’s suitability for the exit option chosen and the notion of what purchasers are looking for. This will become clearer from what follows below.

Generally speaking, most types of businesses qualify for a family succession. However, if the successor is required to borrow money against the business’s assets to acquire the business, the business will need to be able to support the borrowings and the successor will need to have a professionally produced business plan demonstrating this ability.

As I have said, the emphasis in family successions is usually more on the suitability of the heir than the suitability of the business, so this question has to be changed to: ‘What are we looking for in the successor?’ This will influence the choice of successor and the way he or she should be groomed for the take over.

We will now look at the steps necessary for grooming (or tailoring) the heir for taking over the business.

As we have pointed out for short-term spreads expected recovery value may be too high for short-term liabilities due to the assumptions of the model. Commercial implementations of the original structural model are more sophisticated, in order to produce more accurate spreads, default probabilities and recovery rates even for short time horizons. While in pure diffusion models with a barrier overnight debt is quasi-riskless, the introduction of a jump process captures the fact that default could be triggered by a sudden, unexpected event. Thus, the jump process is appropriate to model the possibility of the firm defaulting instantaneously due to the arrival of negative information with respect to, for example, litigation or fraud.

The traditional fundamental approach and structural models generally are based on the same set of balance sheet inputs. But while the fundamental approach used by most credit analysts requires thorough company and industry knowledge and is therefore rather costly and time-consuming, equity-based models are an efficient means to screen broad universes of credit issuers. However, structural models allow to incorporate credit analysts’ forecasts to take account of qualitative information that is not yet reflected in the balance sheet. Projections can be used to create more realistic estimates of the default threshold or to generate different scenarios with respect to future liabilities.

The bear market for credit between 1997 and mid-2002 has put a new focus on valuing corporate credit. The debt-financed equity bull market of the second half of the 1990s was accompanied by historically high default rates and investigations of the management and reporting of corporate balance sheets.

Obviously the standard approach of using rating agency credit ratings to gauge credit risk is no longer sufficient. As a consequence, quantitative approaches have recently gained popularity, particularly structural models based on equity-market inputs. Quantitative models can be used as a tool to provide warning signals or to determine whether the spread on a corporate bond adequately compensates the investor for the risk. Due to the current low-yield/low-return environment the number of investors interested in credit products has grown worldwide. Credit models like KMV or CreditGrades have been developed to meet the growing investor demand.

These enhancements of the Merton model are able to incorporate companyspecific details and can include subjective credit analyst views. With respect to the rapidly expanding credit derivatives market, quantitative models provide critical inputs for valuation and hedging. Default correlation, a major driver for the valuation of credit portfolio products, can be modeled in both structural and reduced form models. Finally, quantitative credit models have become indispensable tools for the risk management of financial institutions.

Although various quantitative models are used by credit investors, two approaches for modeling default have gained widespread acceptance: structural models and reduced-form models. Both of these methods provide estimates of default probabilities or fair market spreads.