The final purpose of my research is only one: Deriving the optimal investment strategy.  This is the underlying question in every paper that I write. And I judge the relevance of all my papers exclusively by how much they advance towards this objective. My current approach to answer this question has two major steps: (i) Determining the expected returns of different investment strategies, and (ii) understanding the risk of these strategies.

From an academic perspective, I provide robust theoretical explanations based on individual rationality (and no frictions) for the stylized facts in asset pricing that other academics are uncapable of understanding based on general risk-based asset pricing theory and individual rationality (without frictions). This often means that I solve the classic puzzles in asset pricing. In particular, my solutions require none of the fantastic assumptions that prevail in the academic literature, such as claims that most (large) market players are "behavioral" (and repeatedly make the same mistakes, instead of learning from the "rational" academics); claims that "frictions" explain persistent long-run patterns, much longer than what agents need to adjust their actions (in contrast to tiny and, most importantly, unexpected short-term price movements); claims of countless custom-made, reverse-engineered risks that academics invent to "explain" individual empirical patterns (and that explain nothing else); nor variations of these narratives. 

So far, I have offered solutions for the size, the value, the momentum, and the equity premium puzzles. These apparent puzzles are largely due to the theoretically unjustified assumption of stable correlations between risk and certain firm characteristics popularized by Fama and French, for example. Indeed, partial least squares predictions of the equity premium based on disaggregated book-to-markets do not work precisely because of these mistakes.

My research lies at the intersection between theoretical and empirical asset pricing. It stresses that we can only possibly start to understand any characteristic-related premium after determining how the risk-characteristic links vary over time, ideally as theoretical functions of the state of the economy. Indeed, forecasting these premiums is an important part of this research agenda. I explain that predictability and analyst disagreement increase in bad times without requiring any type of agent irrationality, and reveal the internal logical inconsistencies in tests that are used to reject the conditional CAPM theory.

Naturally, I work on investment strategies related to these puzzles, grounded on the theory that I develop. I have created "factor timing" macro-finance strategies, carry trade timing, standard market timing strategies, and substantially raised the Sharpe ratio of the value premium with a better proxy for expected cash flows, based on the correct theoretical explanation for the size and value premiums, for example. I also report here the historical performance of two investment strategies that I developed, based on the joint solution to all these puzzles.

Oh, and I am originally an Engineer. So I approach Economics and Finance as real sciences, unlike most academics in these fields. In fact, explaining something to referees of the top 3 journals in Finance always reminded me of this video.