Previous article discussed a model where dealers quote bid and ask prices that deviate from the fundamental value of the asset in order to offset the adverse selection costs that arise in the case of asymmetric information. We therefore assumed risk neutrality, so that dealers would be concerned only with adverse selection costs. In real markets, however, dealers also act as mandatory liquidity suppliers and are obliged to quote prices continuously. This means they will frequently hold undesired portfolio positions that do not lie on their efficient frontier. The costs that dealers must sustain for holding undesired positions – called ‘inventory costs’ – are another determinant of the bid–ask spread. In fact, through opposite changes in the bid–ask quotations, dealers can encourage transactions by their customers that will rebalance their portfolio. Clearly, in this context, it is crucial to assume that dealers are risk-averse, since only the riskaverse are concerned about the possible losses due to future adverse price changes.

Inventory models assign an important role to market-makers who offer the opportunity to trade at all times and therefore act as immediacy providers. The initial modelling approach (Garman, 1976) to the market-makers’ control problem assumes that their objective is to avoid bankruptcy (the ‘ruin problem’), which could be caused by the uncertainty induced by the arrival of non-synchronous buy and sell orders. As O’Hara (1995) suggests, this approach is not realistic since it assumes that a dealer quotes his prices only at the beginning of the trading game, so his inventory plays no role in the decision.

Your early market search and preliminary patent search are both types of research for which the only cost is some of your time and they are important educational phases in the development of your invention. Your first step will be to check out every store in your local area where such an item as you envision might be offered for sale. If, for example, your idea is for a new type of kitchen gadget, you will certainly want to check the kitchen specialty stores. But, you will also want to check any and every store that sells kitchen gadgets. This means that you might find yourself looking in stores such as Wal-Mart, Target, your local grocery store, the hardware store, the corner convenience store, the department stores at the mall and even the stores that specialize in unusual items, such as Brookstone or Sharper Image. You will need to be creative in thinking of all of the places where an item such as the one you envision might be offered for sale.

Intuitively, the described long-term pattern contrasts with the much more cyclical behavior of credit spreads. Yet it should be noted that a large part of this deviation has to be attributed to changes in the databases of the rating agencies and the average quality of recent new issuance. When the database contains more investment grade companies, default rates naturally tend to be lower, and vice versa. Furthermore, historical data on default rates does not only reflect the broad credit cycle, but also changes in companies’ preferences towards bank debt and corporate issuance. When banks’ lending standards are particularly restrictive, especially companies with a lower credit quality may prefer to finance their business by issuing corporate bonds. For the high-yield market there is empirical evidence that the average maturity of outstanding debt is correlated with the probability of default. In other words, default probability changes over the life of a bond. While at the date of issuance the company has sufficient capital, there is often considerable uncertainty about the viability of the business model and future economic success. Together with the 1990/91 recession the enormous volume of junk bonds issuance that took place in the late 1980s is responsible for the peak in default rates in 1991. Consequently, default rate data provided by the rating agencies is not a very pure indicator of credit conditions through time.