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Recently, due to its passive property, the smart beta has become one of the most interest topics in searching the alpha. In this paper, we attempt to show whether the smart beta strategy generate abnormal excess return, in tradition, which are known as the exclusive property of active fund. Further, we attempt to verify the key drivers of the alpha in the smart beta portfolios. For this purpose, we categorize various smart beta strategies by their scheme for asset picking and risk reduction. Then, based on our categorization, we evaluate and analyze the performance of smart beta strategy in perspective. Our empirical analyses show following results: applying alternative risk reduction scheme to traditional market index portfolio would results in enhanced efficiency; however, without combining any asset picking scheme, the performance of the smart beta portfolio seems explained by the Fama-French 3 factor. Our results lead us to conjecture that it is not the portfolio weighting scheme alone but in association with asset selection scheme that generate significant alpha in the smart beta strategy. In actual practice, our results imply that any passive fund may succeed in seeking the alpha without active strategy, thereby avoiding the risk of market timing and saving the management cost.

This paper introduces a monopolistic competition model containing retail investors with imperfect knowledge and issuers offering complex structured products. The model, for which we provide empirical evidences supporting the issuer’s profiteering by increasing the product complexity, can explain that knowledge asymmetry is the key for the issuer to offer complex product and to enjoy the higher excess profit, thus worsening allocative efficiency. Our empirical analysis reports monotonically increasing mark-up premia, and J-shaped issue amounts with respect to complexity: the former result could be explained in a rational framework considering issuer costs, however, the latter is not the case. Our model proves the empirical results are well explained when knowledge asymmetry between issuer and investors is a strictly increasing convex function of complexity.

The purpose of this paper is to review the risk categories which are predominant in international projects and to rank them according to their effect on project success.

A literature survey of peer-reviewed journal articles, survey reports and books on project management is used as the research methodology. One among the various multi-criteria decision making methods named as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) has been used to rank the risk categories according to their importance. The data for TOPSIS were collected through questionnaire as the research instrument.

The findings derived from evaluation of the publications led to the identification of eight different types of risk categories associated with international projects. The TOPSIS method resulted into political risks, technical risks and design-related risks as the top three risk categories in international projects. Contractual and legal risks and fraudulent practices-related risks are relatively low-ranked risk category.

The findings will be useful in successful implementation of international projects as the knowledge of risk categories and their ranking will help project manager to plan the risk response strategies. A larger sample size for decision makers and more variety of projects can give more exhaustive risk categories and their ranking.

This paper explores eight different risk categories in international projects. It represents the ranking of risk categories according to their importance in project success. This will be helpful to project managers for developing a general framework for planning the appropriate risk response strategies.

Governments of many countries around the world are encouraging their industries to undertake and successfully complete projects in foreign countries. However, many industries experience failure in projects as they fail to implement the risk management (RM) effectively in international projects. This research work provides the risk categories in international projects and their ranking which can assist in developing strategies to respond the risk appropriately.

This paper uses the TOPSIS method for ranking major types of risk categories in international projects. It might represent new opportunities for rigorous and relevant research that would contribute to an in-depth knowledge of RM methodologies.