We present results from a highly powered online experiment with 937 participants on Amazon Mechanical Turk (MTurk) that examined whether MTurkers exhibit myopic loss aversion (MLA). The experiment consisted of measuring MLA-compliant behavior in two between-subjects treatments that differed only...

We introduce a training intervention based on a novel tool to mitigate behavior consistent with myopic loss aversion (MLA). We present the results of a large-scale online experiment with 894 student participants. The study featured a two-step debiasing training intervention based on experience...

Narrow bracketing in combination with loss aversion has been shown to reduce individual risk-taking. This is known as myopic loss aversion (MLA) and has been corroborated by many studies. Recent evidence has contested this notion indicating that MLA's applicability is confined to highly...

Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail-correlation matrices based on Value-at-Risk (VaR) estimates. We demonstrate how to obtain more efficient...

Since the enactment of Pension Protection Act of 2006, lifecycle funds that reduce exposure to stocks with age have rapidly replaced money market funds as the most commonly nominated default investment options for participant-directed retirement plans. We examine their appropriateness in meeting...

Most socially responsible investment funds combine a sustainability objective with a tracking error constraint. We characterize the impact of a sustainability constraint on the mean-tracking error efficient frontier and illustrate this on a universe of US stocks for the period 2003–2010.

We prove a formula for the computation of optimal financial investments in an expected utility framework with arbitrary (not necessarily concave) utility functions. This extends classical results on optimal financial investments for strictly concave utility functions and is of importance...