This study is exploratory research on a relationship between changes in cultivated area of major crops and farm income by regions. We investigated level of income, volatility of income, and migration of suitable region by climate changes as factors influencing changes in cultivated area. Research processes are as follows. First, we classify the regions where cultivated areas are expanded or reduced through the trends of cultivated area by region and crop during recent 10 years. Second, we compare the changes in income related factors between groups during the same periods. Finally, the results from portfolio analysis show changes in stable income-based optimal crops. From these procedures, we found that the changes in cultivated area are not simply explained by income-related factors. In cases of vegetables, however, we also found that high volatility of income could contribute to reduce cultivated area of the crops. The results from portfolio analysis are not always consistent in all of cases. This means that crop selection can be decided by other factors than stable income.

This study aimed to examine the applicability of a portfolio approach to the ecosystem-based fisheries management targeting the large purse seine fishery. Most fisheries are targeting multispecies and species are biologically and technically interacted each other. It enables a portfolio approach to be applied to find optimal production of each species through expected returns and risk analyses. Under specific assumptions on the harvest quota by species, efficient risk-return frontiers were generated and they showed a combination of optimal production level. Comparisons between portfolio and actual production provided a useful information for targeting strategy and management. Results also showed the possibility of effective multispecies fisheries management by imposing constraints on each species such as total allowable catch quotas.

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic prog

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk. The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic programming problem. Since it is now computationally practical to solve the model, a number of alternative models to overcome this complexity have been proposed. In this paper, among the alternatives, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we developed an algorithm to obtain an optimal portfolio from the MAD model. We showed mathematically that the algorithm can solve the problem to optimality. We tested it using the real data from the Korean Stock Market. The results coincide with our expectation that the method can solve a variety of problems in a reasonable computational time.

The portfolio selection is one of the most important and vital decisions that a real or legal person, who invests in stock market, should make. The main purpose of this article is the determination of the optimal portfolio with regard to relations among stock returns of companies which are active in Tehran’s stock market. For achieving this goal, weekly statistics of company’s stocks since Farvardin 1389 until Esfand 1390, has been used. For analyzing statistics and information and examination of stocks of companies which has change in returns, factors analysis approach and clustering analysis has been used (FC approach). With using multivariate analysis and with the aim of reducing the unsystematic risk, a financial portfoliois formed. At last but not least, results of choosing the optimal portfolio rather than randomly choosing a portfolio are given.