cyclical. Th ese contrasting characteristics
of value and momentum investment
“We fi nd that zero-investment value and
strategies have prompted some authors
to combine value and momentum into a
momentum strategies outperform the market
single trading strategy. For example,
Asness (1997) fi nds that following a
over the full sample”
zero-investment strategy that is long in
low-value, high-momentum stocks and Our results are promising. Consistent with previous studies, we fi nd
short in low-value, low-momentum that zero-investment value and momentum strategies outperform the
stocks, produces superior returns. Th e market over the full sample from 1995 to 2004, although both are highly
same is true for a zero-investment volatile and each displays prolonged periods of underperformance.
strategy that is long in high-value, However, the forecasting models for both strategies are able to capture
low-momentum stocks and short in much of this cyclicality. Incorporating these forecasts into the Black-
low-value, low-momentum stocks. Litterman model, we are able to track the market benchmark at any
However, a potential problem with value desired tracking error level under full investment, long-only and beta-
and momentum investment strategies neutral constraints, while producing an average investment
– and strategies that combine the two – outperformance of up to 0.7% a year, even after allowing for substantial
is that they are likely to lead to transaction costs. Our results therefore off er investment managers a viable
substantial departures from client- combined value and momentum investment strategy that is consistent
assigned benchmarks, such as those with the need to follow a specifi c client-assigned benchmark.
based on diversifi ed equity indices. As a
consequence, investment managers are CONSTRUCTION OF VALUE AND MOMENTUM PORTFOLIOS
likely to be reluctant to pursue pure For the purpose of this study, momentum is defi ned as the average
value and momentum strategies in spite monthly return over the previous six months. Since our sample starts in
of the favourable risk-return trade-off January 1995, the fi rst month in which the momentum indicator is
that they ostensibly off er. defi ned is June 1995. Value is defi ned using a combination of dividend
We address this problem by yield, earnings-to-price, book-to-market and cash-to-price ratios. Th ese
implementing a combined value and ratios are calculated on a country-corrected basis along the lines of
momentum strategy using the portfolio Asness, Porter and Stevens (2000). Th at is, each month we subtract from
optimisation model of Black and each valuation ratio for each country index the value-weighted ratio for
Litterman. As an illustration, we apply that country for that particular month. Th is removes any bias that may
the Black-Litterman approach to a global arise from systematic diff erences in valuation ratios across countries. At
investment universe that comprises 177 each month end, we sort the indices in increasing order according to the
national industry indices for the US, the momentum indicator and assign the indices to quintiles where Q1 and
UK and Japan. Our combination of Q5 are the low momentum quintile and high momentum quintile,
value and momentum investment respectively. Within each of the Q1 and Q5 quintiles, we sort in
strategies builds on previous research in increasing order by each value variable (DY, EP, BM and CP). We then
the literature. compute the arithmetic average rank across the four value variables for
First, we extend the fi ndings of Bird each of the Q1 and Q5 quintiles. We call this the Composite Value
and Whitaker (2004) by using an Average Rank. We then re-rank the Q1 quintile by the Composite Value
expanded set of measures to screen for Average Rank, assigning each index to one of fi ve value quintiles, where
value and momentum. Second, we use a Q11 is the low-momentum low-value portfolio and Q15 is the low-
regression approach to forecast the momentum high-value portfolio. Th e same two-way sort is applied to the
relative performance of value and Q5 quintile, yielding a high-momentum low-value portfolio, Q51, and a
momentum investment strategies, high-momentum high-value portfolio, Q55.
conditioning on the US term spread and We next construct two zero-investment strategies. Th e fi rst, which
the aggregate book-to-market ratio, represents a pure momentum strategy, comprises a long position in
respectively. Th e aim is to form a set of Q51 and a short position in Q11. Th e second, which represents a pure
out-of-sample return forecasts that value strategy, comprises a long position in Q15 and a short position in
exploit the cyclical nature of value and Q11. Note that both the momentum and value strategies are defi ned
momentum strategies, and which can be relative to the Q11 portfolio. Th is portfolio should be unattractive to
incorporated into a broader portfolio investors from both a momentum and a value perspective, and is
formation process. therefore expected to underperform relative to all other portfolios
40 SUMMER 2009
39-4139-41 academic.indd 40academic.indd 40 1/6/091/6/09 12:08:1412:08:14Professional Investor Summer 09.42 42 4/6/09 15:41:01
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