Optimizing Optimization: The Next Generation of Optimization Applications and Theory (Quantitative Finance)

20 Optimizing Optimization

This sort of situation would arise when the overall benchmark and the indi-
vidual fund benchmarks are very different, e.g., in the case where the overall
benchmark is a market index and the individual funds are a sector fund and
a value fund. It is unlikely to occur when both the overall and individual fund
benchmarks are very similar, for instance, when they are all market indexes.
Figure 1.14 shows the tracking errors when the combined fund is optimized
with the objective of minimizing tracking error against the combined bench-
mark, subject to the constraints on alpha for each of the funds, but without the
constraints on the individual fund tracking errors.
Figure 1.15 shows the results of optimizing including the SOCP constraints
on the tracking errors for the individual funds.
From the organization’s perspective, using SOCP to constrain the individual fund
tracking errors whilst minimizing the overall fund tracking error should achieve

Overall

benchmark

Tracking error (%)

3.5

3

2.5

2

1.5

1

0.5

0

Benchmark

for fund 1

Benchmark

for fund 2

Figure 1.13 Tracking errors when optimizing funds individually.

Overall

benchmark

Tracking error (%)

3.5

3

2.5

2

1.5

1

0.5

0

Benchmark

for fund1

Benchmark

for fund 2

Figure 1.14 Tracking errors when optimizing funds together.