درخت حوزه‌های تخصصی

Due to the rapid advancements in computer technology, researchers are attracted to solving challenging problems in many different fields. The price of rainbow options is an interesting problem in financial fields and risk management. When there is no closed-form solution to some options, numerical methods must be used. Choosing a suitable numerical method involves the most appropriate combination of criteria for speed, accuracy, simplicity and generality. Monte Carlo simulation methods and traditional numerical methods have expensive repetitive computations and unrealistic assumptions on the model. Deep learning provides an effective and efficient method for options pricing. In this paper, the closed-form formula or Monte-Carlo simulation are used to generate data in European and Asian rainbow option prices for the deep learning model. The results confirm that the deep learning model can price the rainbow options more accurately with less computation time than Monte-Carlo simulation.

This study is a structural equation modeling study. It has investigated the effect of literary tourism during the Covid-19 virus pandemic on tourists' behavioral goals through the attitude of mental norms. The present study is a one-section survey. The statistical population of this study includes all tourists who visited the cultural and spiritual sites of Shiraz, like Hafez and Saadi tombs. Literary tourism is a concept that praises the culture and heritage of a destination. The concept is to go to locations worldwide highlighted in some non/fictional novels. They can fascinate new tourists, increase the number of domestic travelers, and promote tourism destinations. Because the sample size is unknown through Cochran's formula with a 95% confidence level, 384 people were selected by the available sampling method. They answered the questionnaire about the effect of literary tourism during the Covid-19 virus pandemic on tourists' behavioral goals. The collected data were analyzed by using Amos software and SPSS. Confirmatory factor analysis, the reliability and validity of the contract measurement model, Cronbach's alpha results (above 0.7), and composite reliability (greater than 0.7) for the reliability and mean of the extracted variance (greater than 0.5) were confirmed. The structural equation model was used to test research hypotheses and the relationships between research variables (spiritual factors, behavioral purpose). The results showed that spiritual variables, in general, have a positive effect on the behavioral goal of tourists through the attitude of tourists' mental norms. This attitude was also recognized as a significant mediator between spiritual perception and behavioral goals. The findings of this study indicate that literary tourism has a positive, significant effect on increasing re-visit tourism destinations through attitude, mental norms, and perceived behavioral control.

So far, readabilityof disclosure concepts and the behavioral features of investors have not been addressed appropriatedly in Iran despite their importance and there is not even a suitable tool to measure it in the country. Therefore, it seems necessary to conduct research in Iran to introduce the concept of disclosure readability, its measurement and the impact of business strategy on the readabilityof disclosure of financial statements. Therefore, the current paper evaluated the effect of the type of business strategy on the readability of financial statements of companies listed on the Tehran Stock Exchange. This is an applied causal (post-event) correlational paper. The statistical population of the study is all companies listed on the Tehran Stock Exchange. Using the systematic elimination sampling method, 129 companies were selected as the research sample and were surveyed in a period of 5 years from 2015 to 2019. EViews 9 and regression were used to test the research hypotheses. The results show that the type of business strategy affects the readability of financial statements of companies listed on the Tehran Stock Exchange.