مطالب

In this paper, the European option pricing is done using neural networks in the Black-Scholes-Vasicek market. The general purpose of this research is to compare the accuracy of neural network and Black-Scholes-Vasicek models for the pricing of call options. In the sequel, the finite difference method is applied to find approximate solutions of partial differential equation related to option pricing in the considered market. In the design of the artificial neural network required for this research, the parameters of the Black-Scholes-Vasicek model have been used as network inputs, as well as 720 data from the daily price of stock options available in the Tehran Stock Exchange market (in 1400) as the network output. The approximate solutions obtained in this article, which were carried out by two methods of neural networks and finite differences on the Tehran stock exchange based on the daily price of stock options, are shown that neural networks are more accurate method comparing with finite difference. The comparison of pricing results using neural networks with real prices in the assumed market is presented and shown via diagram, as well. In this paper, the European option pricing is done using neural networks in the Black-Scholes-Vasicek market. The general purpose of this research is to compare the accuracy of neural network and Black-Scholes-Vasicek models for the pricing of call options. In the sequel, the finite difference method is applied to find approximate solutions of partial differential equation related to option pricing in the considered market. In the design of the artificial neural network required for this research, the parameters of the Black-Scholes-Vasicek model have been used as network inputs, as well as 720 data from the daily price of stock options available in the Tehran Stock Exchange market (in 1400) as the network output. The approximate solutions obtained in this article, which were carried out by two methods of neural networks and finite differences on the Tehran stock exchange based on the daily price of stock options, are shown that neural networks are more accurate method comparing with finite difference. The comparison of pricing results using neural networks with real prices in the assumed market is presented and shown via diagram, as well.

Objective: The aim of this study was to compare the effectiveness of mindfulness-based therapy and transactional analysis on sexual function and sexual satisfaction in female patients with bipolar disorder. Methods: In this study, 20 women with bipolar disorder who referred to the Gyrus Specialty Neurology and Psychiatry Clinic in Tehran from April to August 2022 were selected through purposive sampling and randomly assigned to three groups: mindfulness-based therapy, transactional analysis therapy, and a control group. All participants completed the Female Sexual Function Index (FSFI) by Rosen et al. (2000) and the Sexual Satisfaction Scale by Larson et al. (1998) before and after the intervention. The mindfulness-based therapy group underwent eight 90-to-120-minute sessions held twice a week, while the transactional analysis group received treatment in nine 60-to-120-minute sessions held twice a week. Data were analyzed using descriptive statistics and repeated measures analysis. Findings: The results indicated that both mindfulness-based therapy and transactional analysis therapy had an effect on sexual function and sexual satisfaction in female patients with bipolar disorder. Moreover, a comparison of the effectiveness of the two therapeutic approaches across all dimensions showed that mindfulness-based therapy had a greater impact on sexual function and sexual satisfaction in female patients with bipolar disorder compared to transactional analysis. Conclusion: Therefore, the use of mindfulness-based therapy is recommended in psychology clinics.

A house is the origin of many bitter and sweet experiences and the place for the formation of people's personality and identity. One of the wonders of creation is the presence of different needs in men and women. Hence, designers and architects need to review architectural design to create mental comfort in houses, which consist of two different genders. This study aimed to investigate gender differences and their impacts on residential spaces to provide suggestions for better housing designs. For this, primary concepts about gender were first raised, and then relevant theories were examined to describe the interaction of the concept of gender in a residential space. In the end, the feasibility of appropriate designs, which help promote the quality of a residential environment, was measured. The study methodology was qualitative, which described a desirable housing space. According to questionnaire analyses and a survey of 20 men and women, it was concluded that women tended to focus on details and kitchens, whereas men valued living rooms and halls. In sum, it was critical to separate public spaces from private spaces and to give characters to spaces. The goal of this study was to investigate the factors that affect desirable housing spaces and residential-architectural criteria in giving gender to spaces. Findings revealed gender differences stemming from cultural, social, and historical aspects; therefore, people's genders, along with other factors such as age, tastes, and needs, should be considered in designing spaces.