We analyse models for panel data that arise in risk allocation problems, when a given set of sources are the cause of … an aggregate risk value. We focus on the modeling and forecasting of proportional contributions to risk. Compositional …

We describe a simple robust technique for incorporating any type of views on expected returns into the Risk parity … remain at risk parity. Second, agnostic (cautious) views always result in a more diversified allocation. We further extend … this framework to arbitrary initial risk budgets, and suggest an alternative to the Black-Litterman methodology …

Analytical portfolio risk calculations can be derived and computed in matrix form. Since the inputs are linear asset … number. Marginal Contributions and Expected Shortfall provide more insight about concentration of risk vs. diversification …

labor-income risk can explain much of this risk-taking pattern. Uncontrollable labor-income risk stresses middle …, middle-income households reduce (controllable) financial risk. Richer households, having less pressure, can afford more risk …-taking. The poor take low risk because they avoid jeopardizing their subsistence consumption. …

We consider an optimal risk-sensitive portfolio allocation problem accounting for the possibility of cascading defaults … contagion effects when making investment decisions, reduces his risk exposure as he becomes more sensitive to risk, and that his … strategy depends non-monotonically on the aggregate risk level …

single intuitive number, defined here as the “crash volatility”, to characterize the true left-tail risk as an alternative to … optimizer to finally “see” the risk effect of the non-Gaussian distribution. An example using Amaranth's returns before it lost … -71% in September, 2006 illustrates how these new techniques caught a much higher level of risk lurking in the data …

We investigate portfolio diversification strategies based on hierarchical clustering. These hierarchical risk parity … strategies use graph theory and unsupervised machine learning to build diversified portfolios by acknowledging the hierarchical … lower tail dependence coefficient. Such innovation is expected to achieve better tail risk management in the context of …

Model risk has a huge impact on any risk measurement procedure and its quantification is therefore a crucial step. In … this paper, we introduce three quantitative measures of model risk when choosing a particular reference model within a … given class: the absolute measure of model risk, the relative measure of model risk and the local measure of model risk …

Risk parity has been considered a heuristic asset allocation method. In this paper, we show that, to the contrary, risk … parity is a special case of a mean-risk type of a portfolio optimization problem with log-regularization to constrain weights … unconstrained mean-risk portfolio and a risk parity (or risk budgeted in general) portfolio. We also demonstrate in a Bayesian …