We investigate the causal structure of financial systems by accounting for contemporaneous relationships. To identify structural parameters, we introduce a novel non-parametric approach that exploits the fact that most financial data empirically exhibit heteroskedasticity. The identification...

Contrary to conventional wisdom in nance, return prediction R2 and optimal portfolio Sharpe ratio generally increase with model parameterization, even when minimal regularization is used. We theoretically characterize the behavior of return prediction models in the high complexity regime, i.e....

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

We investigate the causal structure of financial systems by accounting for contemporaneous relationships. To identify structural parameters, we introduce a novel non-parametric approach that exploits the fact that most financial data empirically exhibit heteroskedasticity. The identification...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance—in terms of SDF Sharpe ratio and average pricing errors—is improving in model parameterization (or “complexity”). Our results predict that the best...

We investigate the performance of non-linear return prediction models in the high complexity regime, i.e., when the number of model parameters exceeds the number of observations. We document a "virtue of complexity" in all asset classes that we study (US equities, international equities, bonds,...

In this paper we examine the nonlinear relation between the EUA price and its fundamentals, such as energy prices, macroeconomic risk factors and weather conditions. By estimating a Markov regime-switching model, we find that the relation between the EUA price and its fundamentals varies over...

In this paper we examine the nonlinear relation between the EUA price and its fundamentals, such as energy prices, macroeconomic risk factors and weather conditions. By estimating a Markov regime-switching model, we find that the relation between the EUA price and its fundamentals varies over...

In this paper we examine the nonlinear relation between the EUA price and its fundamentals, such as energy prices, macroeconomic risk factors and weather conditions. By estimating a Markov regime-switching model, we find that the relation between the EUA price and its fundamentals varies over...

In this paper we examine the nonlinear relation between the EUA price and its fundamentals, such as energy prices, macroeconomic risk factors and weather conditions. By estimating a Markov regime-switching model, we find that the relation between the EUA price and its fundamentals varies over...