EDHEC Business School

About: EDHEC Business School is a education organization based out in Roubaix, France. It is known for research contribution in the topics: Portfolio & Capital asset pricing model. The organization has 294 authors who have published 1749 publications receiving 42687 citations. The organization is also known as: Ecole des Hautes Etudes Commerciales du Nord & EDHEC Business School.

Revisiting Mutual Fund Performance Evaluation

Abstract: Mutual fund manager excess performance should be measured relative to their self-reported benchmark rather than the return of a passive portfolio with the same risk characteristics. Ignoring the self-reported benchmark results in different measurement of stock selection and timing components of excess performance. We revisit baseline empirical evidence fund performance evaluation utilizing stock selection and timing measures that incorporate the self-reported benchmark. We introduce a new factor exposure based approach for measuring the – static and dynamic – timing capabilities of mutual fund managers. We overall conclude that current studies are likely to be misstating skill because they ignore the managers’ self-reported benchmark in the performance evaluation process.

Can We Predict Stock Market Crashes

Abstract: In this article, the authors suggest how to think about a new framework for the analysis of financial bubbles and a possible vector of variables able to signal when an economy enters a state of disequilibrium. The working hypothesis is that market crashes are preceded by a bubble. The authors define a bubble as an anomalous increase in asset prices with respect to the economy. An exponentially growing spread between asset prices and the economy is therefore an indicator of the probability that a bubble is in the making. However, as the authors point out, this indicator alone is not sufficient as anomalous price growth can be generated by different macroeconomic scenarios. The authors discuss different macroscenarios that can lead to bubbles and the related indicators.

Order from Chaos: How Data Science is Revolutionizing Investment Practice

Abstract: In this article we describe some of the limitations of the econometrics toolkit, and how financial data science is helping overcome those limitations.

What Shapes Consumer Choice and Financial Products? - A Review

Abstract: This review looks into the developments in consumer finance: what we now know about the various aspects of household finance, and which research directions can yield meaningful impact on consumer welfare as well as that of other stakeholders in the ecosystem. Rather than a comprehensive survey, we focus on the areas that affect consumer choice and discuss each in context of research in consumer credit, housing and mortgage debts, and retail investment products. The sub-fields that we cover are consumer behavior and biases, financial literacy and education, financial product design and marketing, regulation and consumer fintech. We also discuss five future research directions and considerations for researchers and policy makers.

Out-of-Sample Equity Premium Predictability and Sample Split Invariant Inference

Abstract: For a comprehensive set of 21 equity premium predictors we find dramatic disagreement between out-of-sample predictability results depending on the choice of the sample split date. To resolve this issue we propose reporting in graphical form the out-of-sample predictability criteria for every possible sample split, and two out-of-sample tests that are invariant to the sample split choice. We provide Monte Carlo evidence for the validity of the bootstrap based inference we propose. We find that many investors making decisions in real time could have benefited from conditional predictions. The in-sample, and the sample split invariant out-of-sample mean and maximum tests that we propose, are in broad agreement. We also show how one can construct sample split invariant out-of-sample predictability tests that simultaneously control for data mining across many variables.