The optimised portfolio the manager selects on the
efficient frontier is a book with an expected return
equivalent to that of the initial fund, and a lower
risk forecast. Alternatives include the book with
maximum expected Sharpe ratio, ie., the highest
expected return/risk combination, or one with
higher expected returns, which would absorb the
overlay implementation costs.
As shown in Fig.2 (overleaf), this new optimisation-
enhanced book still reflects the initial stock
convictions. Only seven of the previous longs (lowest
positive scores) now turn into zero-weight positions.
Risk results differ from the original book, with a
lower volatility (18% vs 30%) for an equivalent
expected return. The risk distribution is much more
balanced than before. The long positions now
consume 60% of the risk budget (vs the previous
36%), for 35% attributed to the shorts (vs 64%). The
new overlay basket provides the expected volatility
dampener to the overall strategy, and takes only 5%
of the total risk budget.
At the stock level, risk contributions from individual
long and short positions have now converged.
Overlay aside, the average risk contribution is 3% (vs
the previous 1.8%) for a long position, and 3.5% (vs
6.3%) for a short one. These new figures are much
more in line with the symmetric scoring model
originally put in place.
Be it through volatility management, or more
consistent portfolio construction, the risk-adjusted
performance of L/S equity portfolios may benefit
from optimisation-assisted enhancements.
Refining the implementation stages
Even those hedge fund managers and prop traders
who resist the idea of segmenting expensive alpha
and cheap beta will find that optimisation tools
are probably already playing a part in the market
implementation of their current strategies.
In times of fierce competition, the ability to identify
the next investment idea (on both longs and shorts)
and convert hypothetical alpha into real profits are
equally important. The