This study analyzes the relationship between information asymmetry and dividend policy in an emerging market, Korea. We adopt several proxies for asymmetry, such as Glosten–Harris Hasbrouk–Foster–Viswanathan models, drawn from market microstructure literature. finds a negative yields, which appears to be particularly strong when firms have difficulty raising external capital because they high s...

As a matter of course, power market uncertainties escalation is by product of power industry restructure on one hand and the unrivalled penetration of renewable energies on the other. Generally, the decision making process in such an uncertain environment faces with different risks. In addition, the performance of real power markets is very close to oligopoly markets, in which, some market play...

introduction: this paper proposes an appropriate strategy for exporting hepatitis b vaccine, manufactured by pasteur institute of iran, to other countries. methods: eeffectiveness factors and their relative variables were found out by factor analysis method in spss software. results: we could identify 6 main factors which can extremely affect the export of this product. we evaluated manufacture...

A common problem for marketing strategists is how to appropriately segment the market and select segment-specific marketing strategies. This paper presents a novel approach which integrates Fuzzy Delphi method, self-organizing maps (SOM) and a visualization technique to cluster customers according to their various characteristic variables and visualize segments by producing colorful market maps...

This paper proposes a dynamic proportion portfolio insurance (DPPI) strategy based on the popular constant proportion portfolio insurance (CPPI) strategy. The constant multiplier in CPPI is generally regarded as the risk multiplier. Since the market changes constantly, we think that the risk multiplier should change according to market conditions. This research identifies risk variables relatin...

In recent years researchers have developed a lot of interest in stock market prediction because of its dynamic & unpredictable nature. Although there were lots of methods of prediction none of them is prove to produce satisfactory results. Machine learning techniques proved to be better than other methods because of its ability of nonlinear mapping. In this paper we survey different input param...