By Edward I. Altman
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Extra resources for Corporate Bond Rating Drift: An Examination of Credit Quality Rating Changes over Time
Because the yields decline over time in this example, when a bond is downgraded, the magnitude of yield decrease (and hence the return attributable to price appreciation) is less than it would be if the bond's rating remains the same. Based on the performance profile in Table 22, Table 23 shows total returns on these five hypothetical bonds and the entire portfolio under the following scenarios: (1) ratings remain unchanged, (2) the rating transition during the holding period follows a stationary Markov chain process, and (3) the rating drift process is a nonstationary Markov chain.
T h s is also possible in our study. That is, a bond's rating could change once or more during time t and time (t+ 1). " The length of time observed for a bond's rating to change or remain unchanged may be an important factor in determining transition probabilities. The underlying process of rating changes is assumed to be described by a first-order transition matrix in the cases of the MKV-S and MS models. A higher order Markovian property is possible; namely, the rating state at time t may depend on the state(s) before time (t-1).
This proportion was only 20 percent for the 1970-79 period. AA-rated bonds tended to have very little chance of an upgrade (less than 3 percent within five years), and fairly uniformly, about 30 percent of the issues could be expected to be downgraded within five years. A-rated bonds had a greater likelihood of upgrades than AA-rated issues, although their downgrades still exceeded their upgrade percentages by about two to one. This ratio has a good deal of statistical significance because the number of observa- CoQorate Bond Rating Drift tions was high and the upgrade proportion was not so low as to make the ratio irrelevant, as was the case for AA-rated issues.