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The worldwide Covid-19 epidemic while affecting numerous places, has had a profound effect on virtual advertising and advertising and, globally, in the provinces and at the neighborhood level. except, this effect for the most element become positive, in contrast to what has seen in exclusive sectors which include economy, human sources, etc., whilst contamination reasons a variety of incapacity amongst clients and advertisers alike, in phrases of welfare, social work, inflation, business, and many others., the equal shifted conduct goes as a long way as running. , investing strength, getting into self-schooling, adopting new programs from the internet, expanding social and hygiene concerns, retaining distance strategies from complete regions, internet-based media willpower, get right of entry to online sources, etc., and this has greatly impacted the display and endorsed efforts. The moral movement has moved past the PC and digital international, which places open doors for advertisers and products to connect with clients more efficiently than ever before. With the arrival of expanded online media and the call for pc-generated content material, the evolved Media have given advertisers a part of the monetary freedom. At the equal time, this has, in turn, enabling advertisers to be extra proactive and to engage with the public at the same time as appearing excessive excellent demonstration programs. The purpose of this study is to explore, investigate, and recognize the effect of coronavirus on the digital market and businesses.

Bank efficiency is essential in the establishment of healthy financial systems in countries. In this respect, bank managers are expected to respond correctly to questions raised about the financial performance of banks, which is practically impossible without examining the efficiency of the branches under their oversight. In most previous studies, Data Envelopment Analysis was used for evaluating the efficiency of financial branches. The large number of evaluation factors in the analysis leads to an increase in the number of efficient units and thus a decrease in the power of discrimination. Taking a systematic view into consideration, in this study, a step-by-step method was developed for selecting the effective factors in the efficiency of different branches of one of the Iranian Banks based on the effect of each factor or indicator on the whole system’s efficiency including the branches under evaluation. To this end, a new method was proposed for the evaluation of system’s efficiency and some of its properties were stated.

Designing trading systems with good returns is critical for capital market investors. Trading systems are often based on a combination of several tools to use their combined information. For the first time in Iran, the present study aimed to propose a pattern detection algorithm for a flag pattern based on Japanese candlestick charts and their arrangement. By recognizing the pattern and if the 4- and 10-day moving average is confirmed, a shopping position is developed, and the selling time is determined based on an optimized and dynamic process commensurate with price changes and the data scale. Our objective was to address the question of whether the returns resulting from this strategy have a more significant positive return compared to the purchase and maintenance strategy. The research sample included the daily information of 16 active companies of basic metals in Tehran Stock Exchange during 2007-2019, extracted from the database of Novin Rahavard software. Data analysis was performed in MATLAB software, and the obtained experimental evidence was described using t-test. According to the results, the research strategy had a higher performance in terms of returns and risks compared to the market.

The occurrence of unexpected phenomena in recent decades in financial markets around the world,led to the development of theories,beyond the defined principles and criteria of classic finance.These theories are based on financial psychology and they are explaining the role of psychology in financial sciences as an influential factor and became irreplaceable in financial markets and investor decisions.One of the important theories in this field is the bounded-rationality-theory,which can explain the behavior of decision-makers about financial and economical issues based on defined theoretical frameworks and assumptions.This study developed the stock pricing model by comparing the predicted stock price based on the bounded-rationality-theory and the real stock price through collecting the data of 122 companies listed on the Tehran Stock Exchange during the period 2011to 2019.The results of this study show the effectiveness of the bounded-rationality-theory based on the separation of stock return components and measuring the irrationality coefficient and emotional reactions of investors' decisions in stock prices.Accordingly,the limitations of investors 'ability to process information seem to affect the level of use of reasoning and rationality in decision-making and the effect of bounded-rationality through the irrationality and limited attention on stock pricing.Therefore,it is expected that knowledge about the process of bounded-rationality based on the rational-bounded of investors and the behavioral biases resulting from the irrational part of their thinking,will provide a good explanation for the process of changes in financial markets.This can provide both profit opportunities and costs in investment management so that it can be used in modeling,analysis and investment strategies.

The financial anomalies, which have brought about challenges for the nature of efficient-market hypothesis, provide ample experimental evidence on the deviation of market from rationality. According to the efficient-market hy-pothesis, investors avail themselves of all the information available in the market, and then attempt a thorough and painstaking interpretation of it. The empirical evidence, however, reveals that most investors fail to imple-ment rigorous information processing, thereby rendering to a number of behavioral theories concerning market inefficiency and biased information processing. The current research sets out to identify and scrutinize the im-pact of the CEO’s perceptual biases in judgment and economic decision-making on the reporting quality of the firms listed on the Tehran Stock Ex-change. The Purpose of this study CEO Overconfidence and Overinvestment by Role of Economic moderators Tehran Stock Exchange (TSE). One hun-dred five companies were selected as the sample size by systematic removal sampling reviewed in 2012-2019. Due to its dichotomous dependent variable, this study uses probit regression to test the research hypotheses. The results indicated the significant positive effect of CEO overconfidence on overin-vestment. It was also noted that Exchange Rate strengthens the positive effect of CEO overconfidence on overinvestment. Based on these results, the CEO's decisions as a decision-maker in charge of any company, especially under inflationary conditions, can play a substantial role in future corporate investment levels. The findings reveal that the indices of the CEO’s percep-tual biases in judgment and economic decision-making exert a significantly negative effect on financial reporting reliability and competitiveness.

Criteria weighting is a crucial step in the entire decision-making process. Determining the appropriate weights will lead to more reliable results. This study aims to use a coalitional game method for calculating proper criteria weights in multi-criteria decision-making (MCDM). In this paper, the Shapley value method is used to determine the weight of criteria. A numerical case study of 65 banks has been used to explain the efficiency of the proposed method. To this end, using the TOPSIS technique, the alternatives are ranked once in Shapley value and again in the Shannon entropy weighted matrix. Then the results are obtained applying Spearman rank correlation coefficient are compared to efficiency-based ranking using data envelopment analysis (DEA) as a powerful benchmarking method. In the proposed method, unlike many conventional weighting methods, the selection of criteria weights is made in a coalitional game with the participation of all criteria; the obtained weights are both intuitively and objectively fairer, and more reliable rankings are provided. According to the logical and fair calculation of weights, having a simple and understandable mathematical method, and no need for experts’ judgment, the proposed method can be used in real problems. Especially where realistic ranking has a significant impact on the equitable allocation and absorption of resources.

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.

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.

The rapid growth and advancement of electronic devices and technologies in the FinTech industry empower new innovative products and services. The covid-19 pandemic could have a devastating effect on Malaysia’s economy, but it has offered additional opportunities for the E-wallet segment of the Fintech business to thrive. The E-wallet segment of FinTech is one of the latest innovations that is currently growing as there is a need for contactless payments during the pandemic situation. The main objective of the study is to examine the factors affecting e-wallet adoption among young adults in Malaysia. A sample of 200 responses was analyzed using Smart PLS 3.0. The findings revealed that the factors of “performance expectancy”, “effort expectancy”, “compatibility”, and “social influence” have a positive and significant impact during the pandemic; however, the factor of “facilitating conditions” has no significant impact on the adoption of the E-wallets. The study substantiates the key and important variables of adoption in order to develop and evolve E-wallet providers' existing services. Particularly, due to the increasing importance of e-commerce, E-wallet service providers are urged to focus on the system's interoperability, which encourages individuals or customers to use the strategy.  They should include unique features that allow customers to accept the service, trust its benefits and feel comfortable using the technology. The study is useful to the E-wallet providers to improve the existing services. The findings also guide the companies offering E-wallets to enhance the usage and adoption of their services.

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.

The human resource management works closely with all the employees in the organization. An HRM must allow the employees to make constructive criticism when there is a need for it. The duty of organizing the company towards achieving their set goals lies in the hands of the HRM. A Human Resource management process can best be distinct as a tool which is utilized to collect, organize, present, keep and share applied information about the human resource of an organization. To this end, this research present a Throughput model framework that describes individuals' decision-making processes in an algorithmic HRM context. The model depicts how perceptions, judgments, and the use of information affect strategy selection, identifying how diverse strategies may be supported by the employment of certain decision-making algorithmic pathways. In focusing on concerns relating to the impact and acceptance of artificial intelligence (AI) integration in HRM, this research draws insights from multidisciplinary theoretical lenses, such as Al-augmented and HRM assimilation processes, AI-mediated social exchange, and the judgment and choice literature. Results highlight the use of algorithmic ethical positions in the adoption of AI for better HRM outcomes in terms of intelligibility and accountability of AI-generated HRM decision-making, which is often underexplored in existing research.