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According to Ball's principles, the most important weakness and shortcoming in the banking sector is the lack of financial resources and lending by banks to other economic sectors. Banks need liquidity to cover fluctuations and expected or unanticipated changes in balance sheet items, as well as to attract new resources for allocation and as a result to earn income. In this regard, in this research, the asymmetric effects of banking monetary law requirements on lending and financial stability of banks admitted to the Tehran Stock Exchange have been investigated. For this purpose, the data of 19 selected banks and financial institutions were used during the period of 2012-2020. The findings of the research showed that the banking monetary law and capital requirements had negative and significant effects on bank lending. It was also observed that the banking monetary law and capital requirements had positive and significant effects on the financial stability of banks. Finally, it was observed that there is a symmetrical convergence relationship between lending power and banking stability with capital requirements and banking monetary law. [ABSTRACT FROM AUTHOR]

Return and risk are significant parameters in selecting an optimal portfolio, depending on the portfolio return distribution. In a stochastic process, the Markov property causes the future distribution of a random process to be measurable according to the state-transition matrix and the initial process state. According to the main idea of the present study in the optimal portfolio selection, portfolio weights are chosen in a way that the Markov property is established for the portfolio return series and the distribution of future portfolio returns is close to the distribution of investor’s expected returns; hence, K-L divergence (Kullback–Leibler divergence) is utilized as a criterion of closeness. Using this idea, an optimal portfolio selection model was designed and implemented in the present study. This optimal portfolio was optimized using a Markov approach and according to historical data of 10 indices on the Tehran Stock Exchange from 2009 to 2022 in a six-member state. The optimal portfolio performance evaluation using the Sharpe ratio and value at risk criteria indicated that the research model had a higher performance than the mean-variance and weight parity models. [ABSTRACT FROM AUTHOR]