Model uncertainty and liquidity

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 like the market for mortgage backed securities or credit derivatives. 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 expected utility would suggest. In this paper, we capture model-uncertainty using an Epstein and Wang [Epstein, L.G., Wang, T., 1994. Intertemporal asset pricing under Knightian uncertainty. Econometrica 62, 283–322] 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. Our infinite-horizon example produces short, dramatic decreases in liquidity even though the underlying environment is stationary. We show how these liquidity crises are closely linked to the uncertainty aversion effect on the optimal portfolio. Effectively, the uncertainty aversion can, at times, limit the ability of the market-maker to hedge a position and thus reduces the desirability of trade, and hence, liquidity.     

An examination of minimum tick sizes on the Tokyo Stock Exchange

In setting a minimum tick size, exchanges balance the competing objectives of lowering transaction costs and encouraging liquidity provision by minimizing stepping-ahead risk. We examine the trade-off between these two types of costs by examining the proportion of time that the quoted spread equals the minimum tick size (PTIMEMIN). We undertake this analysis on the Tokyo Stock Exchange, a market that sets nine different tick sizes based on stock price. PTIMEMIN varies markedly across stocks, ranging from almost 0 to almost 100 percent. We find that trade size, the number of trades, and price are the most important determinants of whether the minimum tick size is a binding constraint. In fact, trade size and number of trades are more significant determinants of tick size constraint than price. Consequently, we argue that tick size should be set based on trading activity and price, rather than price alone.     

Do reductions in tick sizes influence liquidity?

On 4 December 1995, the Australian Stock Exchange reduced the minimum tick size for stocks priced below $A0.50 and stocks priced above $A10. We use this natural experiment to examine the impact of tick size reductions on liquidity. The present paper reports that although lower tick sizes generally lead to increased liquidity, this result is not universal. Stocks with larger relative tick sizes experience the greatest improvement in liquidity, while stocks with small relative tick sizes and low trading volume experience reduced liquidity. There is no change in order exposure as a result of the reduced tick sizes.     

Schedule evaluation in unstable manufacturing environments

This paper provides a new approach to validate the feasibility of schedules of multiple-step mixed-model unstable manufacturing environments with different changeover times. Traditionally, continuous lines in a manufacturing process run the same sequence in order to minimize WIP inventory and lead time. Nevertheless, multiple reasons such as different product mixes or setup times can lead managers to run different sequences in continuous lines. Unfortunately, lack of reliability of supply and demand in these environments makes it difficult to manage product inventories and often leads to starvation due to the discoordination between the schedules of both lines. This approach is based on a new type of visual representation of schedules and an estimate the probability of starvation. It assumes stochastic supply and demand and a predefined schedule sequence based on batches of different sizes.     

Dynamics and Long-run Structure in U.S. Meat Demand

Empirical analysis, based on a general dynamic Almost Ideal Demand System, shows the commonly used autoregressive and partial adjustment processes are restrictive to meat demand data. This study derives a linear specification in levels form to investigate dynamics in a general framework. Merging a long-run steady state structure with short-run dynamics results in consistent and robust long-run demand elasticities Une analyse empirique, basée sur un systéme dynamique général de demande quasi optimale, montre que les mécanismes courants d'ajustement autorégressif et d'ajustement partiel ont un effect restrictif sur l'évaluation des données de la demande de viande. Les auteurs proposent une spécifcation linéaire par niveaux pour examiner la dynamique du cadre général. La combinaison d'une structure stable de longue durée avec une dynamique de courte période a produit des élasticités cohérentes et solides de la demande à long terme     

The Foreclosure–House Price Nexus: A Panel VAR Model for U.S. States, 1981–2009

Despite housing's economic importance, little has been written on how foreclosures and home prices interact in a framework that includes macroeconomic and housing variables such as employment, permits or sales. Panel VAR results for quarterly state‐level data indicate that price–foreclosure linkages run both ways. Foreclosures negatively impact home prices. The negative impact of prices on foreclosures, however, is much larger. These results suggest the low‐frequency association observed between foreclosures and prices is mostly driven by the endogenous adjustment of foreclosures to prices via the strategic choices of homeowners and lenders, rather than through the effects of foreclosures on home prices.