This analysis aims at developing forecasting models for both commodity volatility and commodity returns based on monthly data. I show that standard models of realized volatility are able to outperform both GARCH models and the random walk in terms of in-sample explanation power and out-of-sample...

If risk aversion and willingness to take on risk are driven by emotions and we as humans are bad at correctly identifying them, the finance profession has a serious challenge at hand—how to reliably identify the individual risk profile of a retail investor or high-net-worth individual. In this...

The integration of ESG factors into the investment process is increasingly becoming mainstream for institutional investors. However, investors struggle with how to incorporate ESG criteria into their top-down asset allocation decisions. In this report we show how ESG criteria can be...

In this paper we argue that investors and investment managers make a mistake if they try to focus on achieving high returns or high risk-adjusted returns and are likely disappointing investors in the long run. Instead, we argue that investment management should focus almost exclusively on...

The financial crisis of 2008 cut deeply into the retirement savings of most retirees and those who are soon to retire. Add to this the clear trends of longer life expectancies and more active retirements and it becomes clear that portfolios must be structured to minimize the risk of asset...

Traditional mean variance optimization assumes that future returns and covariances of all the assets in the universe are known exactly. In practice, these input parameters are subject to estimation errors that may render the output of the optimization algorithm essentially useless. Here we...