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abstract

Market neutral funds are commonly advertised as alternative investments that offer returns which are uncorrelated with the broad market. Utilizing recent advances in financial econometrics, we demonstrate that using standard forecasting methods to construct market (beta) neutral funds is often very inaccurate. Our findings demonstrate that the econometric methods that are commonly employed for forecasting the beta (systematic) risk typically lack sufficient accuracy to permit the successful construction of market neutral portfolios. The results in this paper also highlight the need for higher frequency returns data to be utilized more commonly. Using daily returns over the past year, we demonstrate an approach that is easy to implement and delivers a substantial improvement, relative to other methods, when attempting to construct a market neutral portfolio. © 2015 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

6. Conclusion

This paper has demonstrated that ex post betas can vary from zero substantially for portfolios constructed with the intention of being beta neutral using standard beta forecasting approaches. Portfolios were constructed both based on momentum and by selecting stocks randomly, in order to increase the general applicability of the results. This leads us to conclude that the inability of equity market neutral funds to exhibit market neutrality in their performance may be attributable largely to the fact that the methods employed in the construction of equity market neutral funds are often unreliable. Beta neutral portfolios may be more achievable in certain specific cases, such as with highly liquid assets and reliable intra-day return measurement, but this is left for future research. In the more general case where daily return measurements are the highest return frequency that is available reliably, we find that the annual realized beta (computed from daily returns over the past year) provides a greater accuracy in the construction of market neutral portfolios at the quarterly frequency than other methods.