MaxVaR with non-Gaussian distributed returns

The common fallacy in risk measurement throughout a long investment horizon is to handle only the terminal risk. This pathology affects Value-at-Risk, hence a recent contribution in the literature has proposed the concept of within-horizon risk as a solution to the problem. The quantification of this type of risk leads to the so called MaxVaR measure, but the assumption of Gaussian distributed returns biases this model. This study analyzes the consequences of non-Gaussian returns to the MaxVaR inference. An example of application to long-term risk management is provided.