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We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behaviour for one firm, our measure considers analyst behaviour for all covered firms. Our general effort measure captures additional information about analyst effort and thus can identify accurate forecasts. We emphasise the importance of investigating analyst behaviour in a larger context and argue that analysts who generally devote substantial forecast effort are also likely to devote substantial effort to a specific firm, even if this effort might not be captured by a firm-specific measure. Empirical results reveal that analysts who devote higher general forecast effort issue more accurate forecasts. Additional investigations show that analysts' career prospects improve with higher general forecast effort. Our measure improves on existing methods as it has higher explanatory power regarding differences in forecast accuracy than the commonly applied effort measure. Additionally, it can address research questions that cannot be examined with a firm-specific measure. It provides a simple but comprehensive way to identify accurate analysts.
Simulating the electromagnetic‐thermal treatment of thin aluminium layers for adhesion improvement
(2015)
A composite layer material used in packaging industry is made from joining layers of different materials using an adhesive. An important processing step in the production of aluminium-containing composites is the surface treatment and consequent coating of adhesive material on the aluminium surface. To increase adhesion strength between aluminium layer and the adhesive material, the foil is heat treated. For efficient heating, induction heating was considered as state-of-the-art treatment process. Due to the complexity of the heating process and the unpredictable nature of the heating source, the control of the process is not yet optimised. In this work, a finite element analysis of the process was established and various process parameters were studied. The process was simplified and modelled in 3D. The numerical model contains an air domain, an aluminium layer and a copper coil fitted with a magnetic field concentrating material. The effect of changing the speed of the aluminium foil (or rolling speed) was studied with the change of the coil current. Statistical analysis was used for generating a general control equation of coil current with changing rolling speed.
High-k perovskite oxide of barium strontium titanate (BST) represents a very attractive multi-functional transducer material for the development of (bio-)chemical sensors. In this work, a Si-based sensor chip containing Pt interdigitated electrodes covered with a thin BST layer (485 nm) has been developed for multi-parameter chemical sensing. The chip has been applied for the contactless measurement of the electrolyte conductivity, the detection of adsorbed charged macromolecules (positively charged polyelectrolytes of polyethylenimine) and the concentration of hydrogen peroxide (H2O2) vapor. The experimental results of functional testing of individual sensors are presented. The mechanism of the BST sensitivity to charged polyelectrolytes and H2O2 vapor has been proposed and discussed.