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RESEARCH PRODUCT

Fooled by Data-Mining: The Real-Life Performance of Market Timing with Moving Averages

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In this paper, we revisit the myths regarding the superior performance of market timing strategies based on moving average and time-series momentum rules. These active timing strategies are very appealing to investors because of their extraordinary simplicity and because they promise substantial advantages over their passive counterparts (see, for example, the paper by M. Faber (2007) "A Quantitative Approach to Tactical Asset Allocation" published in the Journal of Wealth Management). However, the ``too good to be true" reported performance of these market timing rules raises a legitimate concern as to whether this performance is realistic and whether investors can expect that future performance will be the same as the documented historical performance. We argue that the reported performance of market timing strategies usually contains a considerable data-mining bias and ignores important market frictions. To address these issues, we perform out-of-sample tests of these two timing models in which we account for realistic transaction costs. Our findings reveal that the performance of market timing strategies is highly overstated, to say the least.