Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Extreme market outcomes are often followed by a lack of liquidity and a lack of trade. This market collapse seems particularly acute for derivative markets where traders rely heavily on a specific empirical model. Asset pricing and trading, in these cases, are intrinsically model dependent. Moreover, observed behavior of traders and institutions suggests that attitudes toward "model uncertainty" may be qualitatively different than Savage rationality would suggest. For example, a large emphasis is placed on "worst-case scenarios" through the pervasive use of "stress testing" and "value-at-risk" calculations. In this paper we use Knightian uncertainty to describe model uncertainty, and use Choquet-expected-utility preferences to characterize investors aversion to this uncertainty. We show that an increase in model uncertainty can lead to a reduction in liquidity as measured by the bid-ask spread set by a monopoly market maker. In addition, the non-standard nature of hedging model uncertainty can lead to broader portfolio adjustment effects like "flight to quality" and "contagion." (Copyright: Elsevier)