This paper evaluates the predictive performance of machine learning techniques in estimating time-varying betas of US stocks. Compared to established estimators, tree-based models and neural networks outperform from both a statistical and an economic perspective. Random forests perform the best...

This paper examines the predictive performance of machine learning methods in estimating the illiquidity of U.S. corporate bonds. We compare the predictive performance of machine learning-based estimators (linear regressions, tree-based models, and neural networks) to that of the most commonly...

Aiming to optimally harvest global equity factor premiums, we investigated the benefits of parametric portfolio policies for timing factors conditioned on time-series predictors and tilting factors based on cross-sectional factor characteristics. We discovered that equity factors are predictably...

Embracing the concept of factor investing, we design a flexible framework for building out different factor completion strategies for traditional multi-asset allocations. Our notion of factor completion comprises a maximally diversified reference portfolio anchored in a multi-asset multi-factor...

We use a dynamic adjustment model and panel methodology to investigate the determinants of a time- varying optimal capital structure. Because firms may temporarily deviate from their optimal capital structure in the presence of adjustment costs, we also endogenize the adjustment process. In...

It is often argued that Black-Scholes (1973) values overstate the subjective value of stock options granted to risk-averse and under-diversified executives. We construct a “representative” Swiss executive and extend the certainty- equivalence approach presented by Hall and Murphy (2002) to...

We use a dynamic framework and panel methodology to investigate the determinants of a firms' time-varying capital structure. Our sample comprises 706 European firms from France, Germany, Italy and the U.K. over the period from 1983 to 2002. If capital structure adjustment is costly, firms may...

Entrepreneurial high-technology start-up firms usually need equity in order to finance their research, product development, and in particular growth opportunities due to new ideas and innovation. In an advanced stage they often require even larger financial resources and may raise equity by...