Since 2008, the German open-ended real estate fund (GOEREF) industry has experienced a critical phase of suspensions of redemption of fund shares, announced fund terminations and, eventually, introduction of a new regulation. With assets under management of over EUR 80 billion, GOEREFs are the...

This paper is the first to analyze and value early exercises of Individual Investors in fixed-income investment products. Assuming decision and transaction costs we consider that a continuous decision-making on holding or exercising is not optimal anymore and propose a new approach to modeling...

Purportedly consistent with "risk parity" (RP) asset allocation, recent studies document compelling "low risk" trading strategies that exploit a persistently negative relation between Sharpe ratios (SRs) and maturity along the U.S. Treasury (UST) term structure. This paper extends this evidence...

The issue of whether the Fama and French (FF) three-factor model is consistent with the propositions of Modigliani and Miller (MM) (1958, 1963) has received surprisingly little attention. Yet, unless it is so, the model is at variance with the foundations of finance. Fama and French (FF) (1993,...

Sénéchal proposes a new analytical framework—the empirical law of active management—to assess the breadth, or diversification, and the skill of a portfolio manager. The framework requires no assumptions regarding a manager’s asset return expectations or investment process. The framework...

This paper examines the impact of birth order on financial decision making. In lieu of explanations such as dissimilar parental style across children with different birth orders (due to learning and experience) or the existence of sibling externalities commonly offered in the literature to...

Machine learning (ML) models for predicting stock returns are typically trained on one-month forward returns. While these models show impressive full-sample gross alphas, their performance net of transaction costs post 2004 is close to zero. By training on longer prediction horizons and using...

We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a combination of Inverse Reinforcement Learning (IRL) and RL. First, the IRL...

We examine portfolio trading and its impact on corporate bond liquidity. Our theoretical framework identifies how portfolio trades provide dealers with benefits through a diversification channel and with costs through a balance sheet channel. We then test empirically multiple hypotheses on the...