Fang Liu, PhD, Finance
Research Interests: Education:
Theoretical and Empirical Asset Pricing, Investment Decision Making, Disaster Risk, Risk Management.
Job Market Paper Title: “Recovering Joint Return Distributions by Linear Regression: Estimation and Applications”
Abstract: I propose a regression approach to recovering the joint return distribution of an individual asset and an aggregate index based on their marginal distributions. This approach relies on the identifying assumption that the conditional return distribution of the asset given the index return is fixed over time. I show how to empirically implement this approach using option prices. I then apply this approach to examine the cross-sectional equity risk premium associated with systematic disaster risk, to estimate the exposure of banks to systemic shocks, and to extend the Ross (Journal of Finance, 2014) recovery theorem to individual assets.
Other Completed Papers
Title: “Performance Evaluation with High Moments and Disaster Risk,” with Ohad Kadan, Journal of Financial Economics, 113, 2014, 131–155
Abstract: Traditional performance evaluation measures do not account for tail events and rare disasters. To address this issue, we reinterpret the riskiness measures of Aumann and Serrano (Journal of Political Economy, 2008) and Foster and Hart (Journal of Political Economy, 2009) as performance indices. We derive the moment properties of these indices and their sensitivity to rare disasters and show that they are consistent with the asset pricing literature. As applications, we show that “anomalous” investment strategies such as “momentum” or investment in private equity lose much of their glamour when accounting for high moments and rare events. Furthermore, using the indices to select mutual funds results in desirable high-moment properties out of sample.
Title: “Generalized Systematic Risk,” with Ohad Kadan and Suying Liu
Abstract: We generalize the concept of “systematic risk” to a broad class of risk measures potentially accounting for high distribution moments, downside risk, rare disasters, as well as other risk attributes. We offer two different approaches. First is an equilibrium framework generalizing the Capital Asset Pricing Model, two-fund separation, and the security market line. Second is an axiomatic approach resulting in a systematic risk measure as the unique solution to a risk allocation problem. Both approaches lead to similar results extending the traditional beta to capture multiple dimensions of risk. The results lend themselves naturally to empirical investigation.
Title: “On Investor Preferences and Mutual Fund Separation,” with Philip Dybvig
Abstract: We extend Cass and Stiglitz's analysis of preference-based mutual fund separation. We show that high degrees of fund separation can be constructed by adding inverse marginal utility functions exhibiting lower degrees of separation. However, this method does not allow us to find all utility functions satisfying fund separation. In general, we do not know how to write the primal utility functions in these models in closed form, but we can do so in the special case of SAHARA utility defined by Chen et al. and for a new class of GOBI preferences introduced here. We show that there is money separation (in which the riskless asset can be one of the funds) if and only if there is a fund (which may not be the riskless asset) with a constant allocation as wealth changes.
- M.S. Financial Mathematics, Stanford University, 2009
- B.A. Finance, Nanjing University (China), 2007
Curriculum Vitae | Email