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ecently a number of authors have examined the hedging performance of R Treasury-bill futures (Ederington, 1979;Franckle, 1980) and foreign currency futures (Dale, 1981; Hi and Schneeweis, 1981, and forthcornin& In order to investigate this question the authors regress the level (or change in the level) of the cash market rate on the level (or change in the level) of the appropriate futures rate over a given hedging horizon (one, two, four weeks, etc.) for some prespecsed sample period. The estimated slope coefficient and R2 of these regressions are respectively viewed as measures of the optimal hedge ratio and the degree of hedging effectiveness.' Often the sample period selected in these studies is quite lengthy. For example, in the foreign currency futures study by Dale (1981), the sample period was over six years. One major problem with using the simple OLS regression model over long periods of time is the underlying assumption that the regression slope coefficient, or, in the case of futures, the optimal hedge ratio, is stable over the whole sample period. Such an assumption seems particularly questionable in view of the considerable volatility and turbulence which have occurred in foreign exchange markets in the post-Smithsonian flexible exchange rate era. In particular, imposing the a priori restriction that regression coefficients are stable over time, when in fact they may be unstable, could significantly bias the estimation of the optimal hedge ratio and therefore the measure of hedging effectiveness. Such misspecification may well result in costly, suboptimal (second best) hedging decisions by market participants.In this article we use three different econometric approaches to examining the question of hedge ratio stability for five foreign currency futures contracts traded on the International Monetary Market (IMM): the Swiss franc, the Canadian dollar, the British pound, the German mark, and the Japanese yen.'The theoretical justification for this methodology within a mean-variance framework has been explored by Ederington (1979) among others.

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We develop distress prediction models for non-financial small and medium enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power to our models. Moreover, industry effects usually demonstrate significance but provide small improvements. The paper contributes to the literature in several ways. First, using a sample with many micro companies, it offers unique insights into European small businesses. Second, it explores distress in a multi-country setting, allowing for regional and country comparisons. Third, the models can capture changes in overall distress rates and co-movements during economic cycles.

This study examines the market reaction to listing on the New York Stock Exchange (NYSE). The marketability gains hypothesis states that investors expect liquidity gains for the less liquid over-the-counter (OTC) stocks but not for their liquid counterparts after their listing on the NYSE. The hypothesis is supported even after accounting for other firm-specific news releases. Stocks with low liquidity on the OTC exhibit a positive reaction, whereas stocks with high liquidity show a non-positive market reaction around the announcement of the listing application. The findings imply that the two different marketplaces, NYSE and OTC, are suitable for stocks with different liquidity characteristics.

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