حسن حیدری

The present study aimed at investigating the effectiveness of metacognitive therapy on dysfunctional beliefs, inflated sense of responsibility, and intolerance of uncertainty in patients with obsessive compulsive-disorder (OCD). The design used in the present study is semi-experimental, pretest-posttest with control group and a tree-month follow-up stage. The statistical population consisted of all patients with OCD in Mahallat, a city located in Markazi province, Iran in 2018. The participants first screened by using inclusion and exclusion criteria. Then sixteen patients with OCD selected as the sample of the study through available sampling method and assigned randomly into two groups: one experimental group and one control group (eight patients in each group). Each participant in the experimental group received 12 treatment sessions according to Well's metacognitive therapy method for OCD. The participants were measured both before and after interventions as well as three months later in the follow-up phase by the Yale-Brown Obsessive-Compulsive Scale (Yale-BOCS; Goodman, 1989), the Obsessive Beliefs Questionnaire (OBQ-44; OCCWG, 2005), the Salkovskis Responsibility Attitude Scale (RAS; Salkovskis, 2000) and the Intolerance of Uncertainty Scale (IUS; Feriston, 1994). Data analyzed by multivariate co-variance analysis. The results indicated that metacognitive therapy had a significant effect on reducing dysfunctional beliefs, the inflated sense of responsibility and the variable intolerance of uncertainty (p˂0.050), and its effect remained three months after treatment (p˂0.050). The findings of the study support the effect of metacognitive therapy in improving the dysfunctional beliefs, inflated sense of responsibility and uncertainty of intolerance in patients with OCD.

Selecting approaches with appropriate accuracy and suitable speed for the purpose of making decision is one of the managers’ challenges. Also investing decision is one of the main decisions of managers and it can be referred to securities transaction in financial markets which is one of the investments approaches. When some assets and barriers of real world have been considered, optimization of stock basket can’t be solved easily, therefore, Meta-Heuristic approach is considered. In this regard, the main goal of this paper is to solve stock portfolio constrained optimization problem by using of Firefly Algorithm (FA) and Imperialist Competitive Algorithm (ICA). In order to do so, daily information of 25 accepted stocks in period of 2010-2016, in Tehran stock market have been used. Results show that Firefly Algorithm (FA) and Imperialist Competitive Algorithm (ICA) showed successful function in constrained optimization of stock portfolio and has acceptable accuracy in finding optimal answers in whole risk and returns levels. Also, the results of comparison of Cardinality Constrained Mean – Variance (CCMV) and Cardinality Constrained Mean – Semi -Variance (CCMSV) portfolios two using of Firefly Algorithm (FA) and Imperialist Competitive Algorithm (ICA) and considering to the findings of two criteria for assessing accuracy in stock basket optimization simultaneously show that Imperialist Competitive Algorithm (ICA) has high speed and accuracy for solving stock basket optimization and could have desirable interaction with real barriers of market. Moreover, there is high accuracy optimization of Cardinality Constrained Mean – Semi -Variance (CCMSV) compared to Cardinality Constrained Mean – Variance (CCMV).

Given the increasing importance of achieving low and stable inflation rate during the last decades, adopting the most suitable practices to implement monetary policies has always been of concern by monetary authorities of different countries. Inflation targeting (IT) regime is the most recent strategy to guide monetary policies that have been introduced following the occurrence of exchange rate targeting and monetary targeting problems. In this respect, in the present research, the performance of a number of IT countries versus that of the non-targeting ones was first investigated employing the difference in difference (DID) method. Then, considering monetary and oil shocks, IT performance in production gap in the economy of Iran was practically examined using smooth transition autoregressive regression (STAR) model. The Results indicated that implementation of IT policy was successful in applying the four main and most influential indicators in the production of treatment countries. In addition, it was revealed that variables such as IT, oil shock, and facility and exchange rates had a statistically negative effect on production shock in the economy of Iran. However, the monetary shock was found to have a statistically positive impact on production shock. Therefore, according to the findings regarding the successful performance of targeting countries, policymakers are recommended to implement IT policy during a long-term interval in order to stabilize it and also provide its prerequisites in the economy of Iran. JEL classification: E31, E58, E52.