This paper is concerned with statistical inference and model evaluation in possibly misspecified and unidentified linear asset-pricing models estimated by maximum likelihood and one-step generalized method of moments. Strikingly, when spurious factors (that is, factors that are uncorrelated with...

We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...

We introduce a simulation-free method to model and forecast multiple asset returns and employ it to investigate the optimal ensemble of features to include when jointly predicting monthly stock and bond excess returns. Our approach builds on the Bayesian Dynamic Linear Models of West and...

We consider the problem of filtering and control in the setting of portfolio optimization in financial markets with random factors that are not directly observable. The example that we present is a commodities portfolio where yields on futures contracts are observed with some noise. Through the...

The asymmetry in the tail dependence between U.S. equity portfolios and the aggregate U.S. market is a well-established property. Given the limited number of observations in the tails of a joint distribution, standard non-parametric measures of tail dependence have poor finite-sample properties...

To capture the well documented time series momentum and reversal in asset price, we develop a continuous-time asset price model, derive the optimal investment strategy theoretically, and test the strategy empirically. We show that, by combining market fundamentals and timing opportunity with...

This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create...

We propose a new methodology for abnormal return detection and correction, and evaluate the economic impacts of outliers on asset allocations with higher-order moments (Cf. Jurczenko et al., 2008). Indeed, extreme returns and outliers greatly affect empirical higher-order moment estimations (Cf....

We propose a new approach to optimal portfolio selection in a downside risk framework that allocates assets by maximizing expected return subject to a shortfall probability constraint, reflecting the typical desire of a risk-averse investor to limit the maximum likely loss. Our empirical results...

I decompose the expected return difference between cross-asset time series momentum and time series momentum into market timing and risk premium components, and show that market timing accounts for 71–79% of the difference. I thus show that two recent critiques of time series momentum do not...