Active asset allocation strategies that use linear asset pricing models now
outperform the strategy based on the characteristics model in terms of a higher
Sharpe performance and more positive abnormal returns. Furthermore, all
strategies that use linear asset pricing models are able to significantly
outperform alternative passive strategies even when the investor faces binding
investment constraints. The improved performance of linear asset pricing
models when we use conditional versions of the models supports a number of
studies from the empirical asset pricing literature that document that
conditional versions of asset pricing models are more able to explain cross-
sectional patterns in stock returns (see Cochrane (1996), Jagannathan and
Wang (1996), Hodrick and Zhang (1996) and Lettau and Ludvigson (2001)).
Our findings support the usefulness of conditional asset pricing models in
forecasting expected excess returns in domestic asset allocation strategies and
provides some support for the use of these models relative to a characteristic
based model of stock returns.
NOTES
1. The momentum effect stems from Jegadeesh and Titman (1993).
2. We focus on expected returns because Merton (1980) points out that estimates of
expected returns are more unstable than the covariance matrix and Best and Grauer
(1991) document the sensitivity of optimal portfolio weights to even small changes in
expected returns.
3. Jagannathan and Ma (2001) find that the sample covariance matrix performs just
as well as other estimators of the covariance matrix when investors face binding
investment constraints.
4. This is set equal to 0.1. Using alternative values of t has no impact on the analysis
for the performance measures used in this study.
5. See Grinblatt and Titman (1989), Chen and Knez (1996) for a discussion of these
points.
6. We do not include the Utilities sector because data is not available for the whole
period.
7. When the characteristics model is estimated, the ln (market value) is used.
8. The FTA index is a value-weighted index of the largest companies on the London
Stock Exchange.
9. Connor and Korajcyzk (1991) regress the demeaned values of the factors on
statistical factors derived from asymptotic principal components analysis.
10. Keim and Stambaugh (1986) and Fama and French (1988) among others also
show that stock and bond returns are partly predictable through time. Fama (1991) and
Cochrane (1999) provide a review of stock return predictability.
ACKNOWLEDGEMENT
Helpful comments received from an anonymous reviewer.
268 JONATHAN FLETCHER

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