FEATURE: ACADEMIC
under all states of the world. A short errors that they generate relative to typical client-assigned benchmarks.
position in this portfolio should We solve this potential problem by incorporating the combined value-
therefore enhance both the momentum momentum strategies into the Black-Litterman portfolio model. Th is model
and value investment strategies. makes it possible for us to deviate from the benchmark only to the extent
We fi rst examine the profi tability of that we express views on certain value-momentum assets. We obtain such
pure value and momentum investment views by forecasting value and momentum returns ex ante. Th ese views are
strategies. combined with the equilibrium expected returns that are imputed from the
At the end of month t in June 1995, we capitalisation weights of the market portfolio. We further impose constraints
form the value and momentum zero- on short-selling, beta-neutrality with respect to the benchmark portfolio, and
investment portfolios and track their three diff erent tracking error levels. Th e out-of-sample performance of the
performance from month t through constrained Black-Litterman portfolio is promising. By following a
month t+6. Our fi rst portfolio is formed conservative policy with respect to the confi dence level with which the views
in June 1995 and we measure portfolio are held, we are able to outperform the benchmark on average, even in the
returns over the next six months from July presence of substantial transaction costs.
1995 to December 1995. We roll this
strategy forward each month until the last
This article is an extract of the full working paper: Babameto, E., and R.D.F.
portfolio formation period in May 2004,
Harris, 2008, ‘Exploiting Predictability in the Returns to Value and Momentum
with performance measured from June Investment Strategies: A Portfolio Approach’, Working Paper 08/09, Xfi Centre
2004 to November 2004. Overall, there
for Finance and Investment, University of Exeter.
are 108 overlapping evaluation periods.
In practice, investment managers face a
variety of constraints (such as the
PROFILE – FACT BOX
requirement that only long positions are
held, or that the portfolio is beta-neutral
Richard Harris
with respect to a particular benchmark). In
Career highlights:
this paper, we adopt the approach of He
Richard Harris is a professor of fi nance in
and Litterman (1999) and use the
the Xfi Centre for Finance and Investment at
Black-Litterman model to generate
the University of Exeter Business School. He
posterior expected returns, and then use
has held visiting positions at the University of
the Markowitz model to derive the
Canterbury and Victoria University of
optimal portfolio subject to a variety of
Wellington, New Zealand, and is currently an
constraints. Here, we impose the following
adjunct professor both at the Norwegian
investment constraints: full investment;
School of Economics and Business
portfolio is long-only; benchmark-neutral Administration, and at the Shanghai
beta; and tracking error constraint. University of Finance and Economics. His
research interests currently include volatility
CONCLUSION modelling and risk management.
Combined value-momentum strategies
have been shown to provide above average
returns while also reducing periods of
Elton Babameto
negative performance. We test the success
Career highlights:
of such strategies by forming two zero-
Elton Babameto is a quantitative equity
investment investment approaches. In our
analyst at HSBC in London. Prior to
global investment universe, consistent
joining the industry, Elton was at the
with the extant literature, such strategies University of Exeter from where he
indeed yield superior returns. However, recieved his masters and a PhD in
the large rewards of our zero-investment Finance. His interests include portfolio
strategies come at the expense of very optimisation/portfolio risk modelling and
high volatility and substantial statistical arbitrage.
idiosyncratic risk. From a practical
perspective, portfolio managers are likely
to be reluctant to pursue such investment
strategies owing to the very large tracking
WWW.CFAUK.ORG PROFESSIONAL INVESTOR 41
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