5 resultados para Market performance

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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Although a large body of literature has focused on the effects of intra-firm differences on export performance, relatively little attention has been devoted to the interaction between firms' selection and international performance and labour market institutions - in contrast with the centrality of the latter to current policy and public debates on the implications of economic globalisation for national policies and institutions. In this paper, we study the effects of labour market unionisation on the process of competitive selection between heterogeneous firms and analyse how the interaction between the two is affected by trade liberalisation between countries with different unionisation patterns.

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This paper sheds new light on a long-standing puzzle in the international finance literature, namely, that exchange rate expectations appear inaccurate and even irrational. We find for a comprehensive dataset that individual forecasters’ performance is skill-based. ‘Superior’ forecasters show consistent ability as their forecasting success holds across currencies. They seem to possess knowledge on the role of fundamentals in explaining exchange rate behavior, as indicated by better interest rate forecasts. Superior forecasters are more experienced than the median forecaster and have fewer personnel responsibilities. Accordingly, foreign exchange markets may function in less puzzling and irrational ways than is often thought.

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This study utilizes a macro-based VAR framework to investigate whether stock portfolios formedon the basis of their value, size and past performance characteristics are affected in a differentialmanner by unexpected US monetary policy actions during the period 1967-2007. Full sample results show that value, small capitalization and past loser stocks are more exposed to monetary policy shocks in comparison to growth, big capitalization and past winner stocks. Subsample analysis, motivated by variation in the realized premia and parameter instability, reveals that monetary policy shocks’ impact on these portfolios is significant and pronounced only during the pre-1983 period.

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In an effort to meet its obligations under the Kyoto Protocol, in 2005 the European Union introduced a cap-and-trade scheme where mandated installations are allocated permits to emit CO2. Financial markets have developed that allow companies to trade these carbon permits. For the EU to achieve reductions in CO2 emissions at a minimum cost, it is necessary that companies make appropriate investments and policymakers design optimal policies. In an effort to clarify the workings of the carbon market, several recent papers have attempted to statistically model it. However, the European carbon market (EU ETS) has many institutional features that potentially impact on daily carbon prices (and associated nancial futures). As a consequence, the carbon market has properties that are quite different from conventional financial assets traded in mature markets. In this paper, we use dynamic model averaging (DMA) in order to forecast in this newly-developing market. DMA is a recently-developed statistical method which has three advantages over conventional approaches. First, it allows the coefficients on the predictors in a forecasting model to change over time. Second, it allows for the entire fore- casting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical bene ts with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the EU ETS market, and that DMA can model these features and forecast accurately compared to conventional approaches. From a policy perspective, we discuss the relative and changing role of different price drivers in the EU ETS. Finally, we document the forecast performance of DMA and discuss how this relates to the efficiency and maturity of this market.

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We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.