اعظم احمدیان

A bank as a business units needs to have liquid assets which can be easily converted into cash at short notice. Thus the concept of liquidity risk management is important for any commercial banks. The impact of liquidity position in management of banks have remained significant, though very elusive in the process of investment analysis vis-à-vis bank portfolio management. In addition, liquidity risk management affects banking performance. In this paper, according to existing theoretical and empirical literature, the suitable system for measuring liquidity risk management is defined. Then, the effect of liquidity risk management on the profitability and survival of banks has been investigated. For this purpose, a model is estimated using panel data method and the financial statements of banks for the period 2005-2017. The results of the study show that there is a significant relationship between risk management and profitability and bank survivability. As poor liquidity risk management reduces the profitability and survival of banks.

Asset-liability mismatch in balance sheet of banks shows serious challenges in banks because of the traditional methods of recording assets and liabilities at book value in Iran. The Central Bank of the country motivated and advised banks to take concrete steps in minimizing the mismatch in the asset-liability composition. This paper attempts to suggest a micro funded framework that can evaluate the role of asset and liability management in banking sector in business cycles through a DSGE model. In this paper, we use Bayesian method to estimate parameters and use national account and balance sheet data from 1981 to 2013. Results show that tightening monetary policy decreases the cost of ALM .On the other hand, raising required reserve requirement increases the cost of asset and liability management; technology shock leads to decrease of asset and liability management cost, and the costs of ALM affects interest rate. Then, the increase of the cost of ALM leads to increase of interest rate. JEL Classification: E31, O42

In financial markets, the main component of risk management is liquidity risk. Asset and Liability Management (ALM) strategy is concerned with managing all risks. Asset and liability management seeks to manage liquidity risk, which refers to both the liquidity of markets and which assets can be translated into cash. The liquidity is importantly affected by the management of banks’ balance sheets. This paper contributes to the discussion by focusing on liquidity and asset and liability management by providing a theoretical framework to examine how the ALM could be reduced the liquidity risk in banking. We investigate the effect of ALM indicators on liquidity risk. We measure liquidity risk, and ALM with indicators approach, using financial statement in 2006-2018 and panel data approach. The results indicate that if asset and liability management improves, liquidity risk decrease and if the ratio of capital adequacy increases, the bank can better cover liquidity risk, and so increasing in capital adequacy will reduce liquidity risk. Deposit per shareholders increases the liquidity risk of banks. Interest rate increases liquidity risk. When profitability increases, liquidity risk will increase. The relation between liquidity risk and profitability is positive.

Understanding the dynamics of productivity shocks is instrumental if we are to identify the sources of economic growth. This paper, investigates dynamic effects of positives productivity shocks to agricultural subsectors during the period from 1991-2015, by disaggregating agricultural sector in Iran into four key subsectors (crops, livestock, fishing and forestry) through an estimated DSGE model. Our Bayesian estimation results suggest that positive productivity shocks lead to an increase in output, consumption, capital, employment and real wages and a fall in marginal costs and price indexes in all four subsectors. Comparing the results across the subsectors shows that following the shocks, generally, crops and livestock have the strongest reactions and forestry has the weakest ones. Additionally, among the variables, output indicates the highest responses to the shocks. Variance decomposition analysis reveals that agricultural fluctuations are mainly explained by productivity, monetary, preference and government spending shocks.

The real macroeconomic instability and frequent changes in the monetary and banking regulations with financial contagion to the banks’ financial statements in the banking network of Iran cause intensified instabilities in its financial behaviors. In this paper, using statistical analysis and three-dimensional charts, we have analyzed the behavior of the financial statements of consolidated balance sheets covering the banking network of Iran. The paper also uses a non-linear estimation to calculate the threshold value regarding financial statements such as the nonperforming loan ratio. Results indicate that the banking network financial statements must be restructured due to exogenous shocks. Also, in the recession periods of the year 2011 fourth period and 2012 first period, the recession has reached the banking network with lag and banks have been able to change the return on assets ratio regimes neither in the year 2011 nor in the beginning months of the year 2012. Furthermore, the banks have started a contracting policy in providing loans. As time passes, yields and the performing loans depict the fact that yields on assets as profit indicators are increased unless the interest earning and different periods of time changes are also augmented. Going beyond the critical threshold, generating loans will be likely to drive non-performing loans since these loans are not going to be reimbursed. Banks will have to extend their loans to new loan contracts to consider them as performing which will lead to identification of fake profits in their statements. Key words: Financial Statement restructuring, Nonlinear Estimation, Threshold value JEL Classification: E21, G21, L2

In this paper we construct a modeling for detection of banks which are experiencing serious problems. Sample and variable set of the study contains 30 banks of Iran during 2006-2014 and their financial ratios. Well known multivariate statistical technique (principal component analysis) was used to explore the basic financial characteristics of the banks, and discriminant Logit and Probit models were estimated based on these characteristics. Results suggest that the model can be used as an analytical decision support tool in both on-site and off-site bank monitoring system to detect the banks which are experiencing serious problems. JEL Classifications: C49, G21, G33