As investors search for new investment vehicles to create value due to ever-increasing competition in the financial markets, the ability to identify sources of potential value creation by addressing society鈥檚 most pressing economic needs has attracted significant attention. Collaboration between experts in finance and technology has emerged as a fertile arena for such value creation. However, the traditional approach to investing in technology has often underperformed, often due to a lack of sufficient diversification and capital efficiency.
On Friday, May 13, members of the Desautels Faculty of Management gathered to celebrate the innovative and impactful research conducted by its scholars.聽
Fifteen professors were on hand to deliver two-minute presentations of their most interesting and research.
Before jumping into the presentations, Dean Yolande Chan took the time to highlight this year's Desautels Faculty Scholar awardees.聽Congratulations to this year's awardees!
Authors: George M. Constantinides and Anisha Ghosh
Publication: Journal of Finance, Vol. 72, No. 1, February 2017
Abstract:
We show that shocks to household consumption growth are negatively skewed, persistent, countercyclical, and drive asset prices. We construct a parsimonious model where heterogeneous households have recursive preferences. A single state variable drives the conditional cross-sectional moments of household consumption growth. The estimated model 铿乼s well the unconditional cross-sectional moments of household consumption growth and the moments of the risk-free rate, equity premium, price-dividend ratio, and aggregate dividend and consumption growth. The model-implied risk-free rate and price-dividend ratio are procyclical, while the market return has countercyclical mean and variance. Finally, household consumption risk explains the cross section of excess returns.
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Authors:听Anisha Ghosh, Christian Julliard, Alex P. Taylor
Publication:听The Review of Financial Studies, Volume 30, No. 2, February 2017
Abstract:听
We consider asset pricing models in which the SDF can be factorized into an observable component and a potentially unobservable one. Using a relative entropy minimization approach, we nonparametrically estimate the SDF and its components. Empirically, we find the SDF has a business-cycle pattern and significant correlations with market crashes and the Fama-French factors. Moreover, we derive novel bounds for the SDF that are tighter and have higher information content than existing ones. We show that commonly used consumption-based SDFs correlate poorly with the estimated one, require high risk aversion to satisfy the bounds and understate market crash risk.
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