Model Uncertainty and Liquidity / Bryan R. Routledge, Stanley E. Zin.

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Routledge, Bryan R

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w8683.Publication details: Cambridge, Mass. National Bureau of Economic Research 2001.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: Extreme market outcomes are often followed by a lack of liquidity and a lack of trade. This market collapse seems particularly acute for markets where traders rely heavily on a specific empirical model such as in derivative markets. Asset pricing and trading, in these cases, are intrinsically model dependent. Moreover, the observed behavior of traders and institutions that places a large emphasis on 'worst-case scenarios'' through the use of 'stress testing'' and 'value-at-risk'' seems different than Savage rationality (expected utility) would suggest. In this paper we capture model-uncertainty explicitly using an Epstein-Wang (1994) uncertainty-averse utility function with an ambiguous underlying asset-returns distribution. To explore the connection of uncertainty with liquidity, we specify a simple market where a monopolist financial intermediary makes a market for a propriety derivative security. The market-maker chooses bid and ask prices for the derivative, then, conditional on trade in this market, chooses an optimal portfolio and consumption. We explore how uncertainty can increase the bid-ask spread and, hence, reduces liquidity. In addition, 'hedge portfolios'' for the market-maker, an important component to understanding spreads, can look very different from those implied by a model without Knightian uncertainty. Our infinite-horizon example produces short, dramatic decreases in liquidity even though the underlying environment is stationary.

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December 2001.

Extreme market outcomes are often followed by a lack of liquidity and a lack of trade. This market collapse seems particularly acute for markets where traders rely heavily on a specific empirical model such as in derivative markets. Asset pricing and trading, in these cases, are intrinsically model dependent. Moreover, the observed behavior of traders and institutions that places a large emphasis on 'worst-case scenarios'' through the use of 'stress testing'' and 'value-at-risk'' seems different than Savage rationality (expected utility) would suggest. In this paper we capture model-uncertainty explicitly using an Epstein-Wang (1994) uncertainty-averse utility function with an ambiguous underlying asset-returns distribution. To explore the connection of uncertainty with liquidity, we specify a simple market where a monopolist financial intermediary makes a market for a propriety derivative security. The market-maker chooses bid and ask prices for the derivative, then, conditional on trade in this market, chooses an optimal portfolio and consumption. We explore how uncertainty can increase the bid-ask spread and, hence, reduces liquidity. In addition, 'hedge portfolios'' for the market-maker, an important component to understanding spreads, can look very different from those implied by a model without Knightian uncertainty. Our infinite-horizon example produces short, dramatic decreases in liquidity even though the underlying environment is stationary.