We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

We build a macroeconomic model for Switzerland, the Euro Area, and the USA that drives the dynamics of several asset classes and the liabilities of a representative Swiss (defined-contribution) pension fund. This encompassing approach allows us to generate correlations between returns on assets...

This paper evaluates the impact of a screening process based on Environment, Social, and Governance (ESG) scores for an otherwise passive portfolio of investment-grade corporate bonds. The main result is that this filtering leads to a substantial improvement of the targeted ESG score without...

Research on socially responsible investment in equity markets initially focused on sin stocks. Since then, the availability of data has been extended substantially and now covers environmental, social, and governance (ESG) criteria. Using ESG scores of firms belonging to the MSCI World universe,...

In a previous paper (Alessandrini and Jondeau, 2020), we demonstrate that in the last decade, investing according to screening based on environmental, social, and governance (ESG) criteria would have allowed investors to considerably improve the ESG quality of their portfolio without...

Long-term investors are often reluctant to invest in assets or strategies that can suffer from large drawdowns. A major challenge for such investors is to gain access to predictions of large drawdowns in order to precisely design strategies minimizing these drawdowns. In this paper, we describe...

Oil price changes fail to predict asset returns because they are too noisy. We construct an oil trend factor that filters out noise and provide evidence that it predicts bond risk premia well. This result holds in developed and emerging countries, both in sample and out of sample. Notably, the...

This paper considers an institutional investor who is implementing a long-term portfolio allocation strategy using forecasts of financial returns. We compare the performance of two competing macro-finance models, an unrestricted Vector AutoRegression (VAR) and a fully structural Dynamic...

We evaluate how non-normality of asset returns and the temporal evolution of volatility and higher moments affects the conditional allocation of wealth. We show that if one neglects these aspects, as would be the case in a mean-variance allocation, a sighifiant cost would arise. The performance...