asset pricing uncertainty premia and design of robust macroeconomic policies. …

specification and estimation uncertainty. We propose a general adjustment of the Value-at-Risk to compute risk measures robust to …

The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability …

We develop a transparent Bayesian approach to quantify uncertainty about linear stochastic discount factor models. We … show that, for a Bayesian decision-maker, the model probability decreases with historical maximum in-sample Sharpe ratios … and increases with model dimensions. We apply our approach to quantify the time series of model uncertainty in North …

Optimal portfolio rules are derived under uncertainty aversion by formulating the portfolio choice problem as a robust …

parameter uncertainty, an important component of model risk. Using a robust approach, we introduce a portfolio rule for … that is robust to parameter uncertainty. Our robust portfolio corresponds theoretically to the global minimum variance …

This paper constructs the probability space underlying the random variable of any time dependent econometric …. Furthermore, it is argued that the probability events belonging to this space are forms of understanding economic activity held by …’s probability space. Finally, a model of the dependencies based on agent-based understandings, and evolution thereof, is presented …