درخت حوزه‌های تخصصی

Performance evaluation, as a tool to know the degree of success of organizations in achieving predetermined goals and a factor in managers' decisions, has been one of the constant needs of organizations. The purpose of this research is to identify performance evaluation indicators and explain the appropriate performance evaluation model in Macro government organizations such as Jam Petrochemical Company. This research is based on the purpose of applied research and also based on the research method with a mixed or combined approach with a sequential exploratory strategy. The required data were collected through qualitative research (interview) and quantitative research (questionnaire). In the quantitative part, the current research can be considered as a non-experimental (descriptive) type of research and a survey type. To analyze the data of the questionnaire, this research has been done in four phases, the first phase is to identify and rank the strengths and weaknesses of Jam Petrochemical Company, and the second phase is to use a Delphi test to identify indicators that are effective in evaluating the performance of Jam Petrochemical Company. The third phase is exploratory factor analysis and determining Dimensions of performance evaluation in Jam Petrochemical Company and finally the fourth phase of structural equations and path analysis. The results of the research showed that considering that the T-statistic for all variables is more significant than 1.96 and also considering the positiveness of the path coefficients, the variables (scientific observation, technology and technology, financial management, managers' responsibility, infrastructure management, management and leadership and human resources) are among the factors that make up the performance evaluation system in Jam Petrochemical Company.

This paper examines the hedging effectiveness of gold futures for the stock market in minimizing variance and downside risks, including value at risk and expected shortfall using data from the Iran emerging capital market during four different sub-periods from December 2008 to August 2018. We employ dynamic conditional correlation models including VARMA-BGARCH (DCC, ADCC, BEKK, and ABEKK) and copula-GARCH with different copula functions to estimate volatilities and conditional correlations between Iran gold futures contract return and Tehran stock exchange main index return. The empirical results reveal that the dynamic conditional correlations switch between positive and near-zero values over the period under study. These correlations are high and positive during the major national currency devaluation and are low near to zero during other times. Out-of-sample one-step-ahead forecasts based on rolling window analysis show that DCC and ADCC multivariate GARCH models outperform other models for variance reduction, while a more interesting finding is that the copula-GARCH model outperforms other models for downside risks reduction.