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Competing academic studies, such as Asness's Fight the Fed Model and Lee, Myers, and Swaminathan's What is the Intrinsic Value of the Dow, offer differing answers to the question of whether equity valuation measures (such as P/E in the case of Asness, DDM in the case of Lee et. al.) can be used to predict the direction of overall equity markets. These are just two seminal studies in the field of market timing, which is itself a part of the broader Tactical Asset Allocation literature.

I would like to know if there are any academic studies (the more recent the better) which use more than one valuation measure/model to try to predict equity market returns, either in absolute terms or relative to fixed income. It would also be interesting if these studies look into what kinds of models may be combined with valuation, such as momentum (see Faber's A Quantitative Approach to Tactical Asset Allocation), in order to yield the best results.

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Take a look at Campbell's 2008 paper "Predicting Excess Stock Returns out of Sample". This paper is in response to Goyal & Welch's paper which argued that excess returns cannot be predicted out of sample. Also see Baekart and Ang's paper "Stock Return Predictability: Is it there?". A good theoretical framework that ties stock return predictability to variables most likely to predict returns is Cochrane's 2008 paper "The Dog that did not bark: A defense of return predictability".

You can identify more recent citations of these papers on Google Scholar for the latest research. However, I would suggest starting here since the key variables, tests, and theory are laid out by the more highly regarded academics.

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