What are the drawbacks of the cell-based approach for bond portfolio construction?
What will be an ideal response?
Let us first describe the cell-based approach. Under the cell-based approach, the benchmark is divided into cells, each cell representing a different characteristic of the benchmark. The most common cells used to break down a benchmark are (1) duration, (2) coupon, (3) maturity, (4) market sectors, (5) credit quality, (6) call factors, and (7) sinking fund features.
The number of cells that the indexer uses will depend on the dollar amount of the portfolio. In
a portfolio of less than $100 million, for example, using a large number of cells entails
a problem. The "drawback" faced by the manager is it would require purchasing odd lots of issues. This increases the cost of buying the issues to represent a cell and thus would increase the portfolio's tracking error. Reducing the number of cells to overcome this problem would increase the portfolio's tracking error in an undesirable way.If the tracking error is unsatisfactory, the manager must alter the portfolio so that the tracking error is within the acceptable range specified by the manager or the client. This is often not a simple process because modifying the portfolio can result in unintended bets (or views) by changing the allocation to cells. This adds another "drawback" to the equation.
Moreover, the cell-based approach faces an additional "drawback" as it ignores how mismatches impact portfolio risk as a result of cross-correlation associated with the risks of each cell. For example, it is possible that there may be large mismatches between two of the cells (characteristics) but the correlation of the risks associated with the cells may result in a very small increase in the portfolio's tracking error.
Fortunately, these drawbacks of the cell-based approach can be dealt with using the more quantitative approach, the multi-factor model approach.
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