Portfolio

This study aimed to investigate the washback effect of three alternative assessment procedures, namely oral-conferences, portfolios, and corpora-based feedback on the writing achievement and attitudes of Iranian EFL university learners. The participants taking part in the study were 156 native Iranian students in a mixed Reading-Writing course. Through the two three-month semesters, the learners were studied in terms of three experimental and one control groups. It should be mentioned that revision was a major component of the pedagogy and learners were asked to incorporate feedback into their revision processes. The findings revealed that the aforementioned assessment procedures led to a significantly better performance of the participants and created a considerable change in their attitudes.

he financial management field has witnessed significant developments in recent years to help decision makers, managers and investors, to made optimal decisions. In this regard, the institutions investment strategies and their evaluation methods continuously change with the rapid transfer of information and access to the fi- nancial data. When information is available as several inputs and output factors, the data envelopment analysis (DEA) applies to calculate the efficiency of com- panies. Distinguishing efficient companies from inefficient ones, makes it possi- ble for the financial managers to select suitable portfolios. The discriminating power of DEA depends on the number of companies under evaluation and the number of inputs and outputs. When the number of inputs and outputs are high compared to the number of units, most of the units will be evaluated as efficient, thus the discriminating power of DEA decreases and the results are not reliable. To deal with this problem, the Quick-Reduct algorithm of the rough set theory (RST) was used in this study to reduce inputs or outputs. It should be noted that the advantage of this algorithm is its ability to use negative data.

These days the use of portfolio assessment is very popular. If it is believed that students at all levels should be doing more than studying for tests; teachers should be doing more than teaching to tests; students should take a more active role in the learning process; and, then the portfolio assessment is an idea worth exploring.. The aim of this study was to introduce portfolio assessment into our classrooms for improving students' reading comprehension. To achieve this goal, the researcher adopted the quasi-experimental design comprising the pretest-treatment-posttest paradigm. Two classes were selected as the experimental and control groups from Cambridge Institute in Sari. They were 52 female students. The only difference between the two groups was integrating portfolio into learning for the experimental group. The result of this study indicated that portfolio assessment did not have a significant effect on the students' reading skill.

Today, the strategy of outsourcing management, in economic enterprises and especially in government organizations, is one of the most important issues in the field of procurement chain management and Strategic Alliance Management. This issue is of special importance in public organizations and institutions. Because these organizations usually have a wide range of missions and supply chains, and according to macro policies and strategies, they need a comprehensive plan for outsourcing. Despite this importance, few studies have addressed the models of outsourcing development in firms. The purpose of this paper is to explain the model of outsourcing development management in the oil and gas industry, based on using content analysis method and deductive approach to the theoretical framework developed in practice through case analysis in Iranian Gas Transmission Company as the company with the most physical assets control on Iran. With this aim, the information required for the research, in addition to the researchers' observation and reviewing the related documents, was obtained through interviews with a significant population of senior managers and experts in the Iranian oil and gas industry. Using theme analysis method, this information was analyzed and the expected situation of the outsourcing development management in the industry, and the impact and interactions, were described and explained.

We seek to determine the optimal amount of the insurer’s investment in all types of assets for a small and closed economy. The goal is to detect the implications and contributions the risk seeker and risk aversion insurer commonly make and the effectiveness in the investment decision. Also, finding the optimum portfolio for each is the main goal of the present study. To this end, we adopted the optimal asset-liability management (ALM) method to control the firm's risk of financial stability and growth by balancing the assets and liabilities of the firm. In the process, stochastic interest rates and inflation risks were taken into account according to the expected utility maximization framework. All assets were established and calculated by the Kalman Filter with the stochastic interest rate following the Hull-White model; an additional stochastic process models the inflation risk. To consider the stochastic process, we employed the geometric Brownian motion in the liability process to ensure a definite liability value. We chose Iran’s Social Security Organization as our sample insurer company since it has a portfolio of five types of assets and four types of liabilities, and operates in a small and closed economy. By Applying the ALM method with the stochastic control theory approach, we acquire the optimal investment strategies for insurers to minimize their risk. Our findings demonstrate the effects of model parameters, such as the degree of risk-taking on the insurer decision.

This study aims at getting a better performance for optimal stock portfolios by modeling stocks prices dynamics through a continuous paths Levy process. To this end, the share prices are simulated using a multi-dimensional geometric Brownian motion model. Then, we use the results to form the optimal portfolio by maximizing the Sharpe ratio and comparing the findings with the outputs of the conventional model. To examine the robustness of the results, we have evaluated its performance for different investment horizons and various volumes of price information over a long period (approximately twenty years) in the Tehran Stock Exchange (TSE). Findings indicate that within the trading dates spanning the interval 24-Mar-2001 to 19-Sep-2020, the return of the portfolios obtained from applying this simulation scheme for maximization of Sharpe ratio is (244% on average) higher and their risk (standard deviation) are lower (1227% on average) than those realized by the conventional methods. Additionally, a comparison of the simulation approach with a performance of the actual market portfolios indicates that the Sharpe ratios of the simulation method are higher (0.055% on average) than those resulting from the total market performances. The results of the stochastic dominance test show that our proposed strategy has a first-order stochastic dominance (FSD) over the conventional one and market portfolios, that means at each level of cumulative distribution, the Sharpe ratio of our method is higher, and as FSD test makes no assumptions about the curvature of investors' utility functions, these results do not depend on the degree of risk aversion of investors, and as long as investors prefer a higher Sharpe ratio, they would be better off if they follow our proposed strategy.

After closing, the multi-period portfolio can be corrected and revised at regular intervals. The philosophy behind using multi-period portfolio models is that investors often have a multi-period view of future changes in assets, which can be the result of technical and fundamental analysis or statistical model analysis. In conventional multi-period portfolio models, it is assumed that the forecast and correction time horizons are the same for all assets. However, one asset may be forecasted over a one-month horizon while another may be forecasted over a two-month horizon, and both may be revised in the future. The purpose of this study is to present a multi-period portfolio model in which assets have different time horizons for corrections or an asset may not be traded for the first few periods and then enter the correction stage. In this model, fuzzy variables defined in a credibility space are used to describe the return, and the credibility measure controls the risk. The model's objective function is to maximize the portfolio's ultimate wealth, and a constraint is used to control portfolio risk, in which the validity of the portfolio's ultimate wealth below a certain threshold is controlled at a certain level of confidence. A combination of particle swarm optimization and simulation is used to find the best solution. Finally, using a numerical example, the model is implemented on a portfolio with 6 assets and 4 monthly time steps on the Tehran Stock Exchange.