محمداسماعیل اعزازی

Asset-liability management (ALM) helps managers achieve their respective objectives by surveilling and controlling the ways through which resources are obtained and allocated. Furthermore, with the help of liquidity management, which sets the required cash by banks for fulfilling costs and other needs (e.g. the cash requested by depositors), ALM controls the risk. In addition, ALM helps managers realize profitability and efficiency of the bank through the application of goal programming (GP) whereby multiple objectives are simultaneously considered when making decisions. In the present research, upon collecting the required data and information, acquiring opinions of experts at a sample bank, and investigating balance sheet of the bank while considering respective constraints, orders of priority of objectives were determined. The results indicated consistency of some items in the balance sheet, such as cash inventory and liability to Central Bank with those set by the model. On the other hand, when it came to some other items, including receivables from the government and credited facilities to public sector, the observed growth was in line with that anticipated by the model. In the meantime, for most items of the balance sheet, including termed deposits and other deposits, investments, and joint activities, the model suggested variable yet positive growths; the growth was higher in demand deposits which are known as less expensive resources, indicating facts about Iranian banking system and Iranian economy where communities are making greater deals of effort to attract this sort of resource.

The main purpose of this study is to determine the real and dynamic relationship between returns and stock market fluctuations in different time horizons so that its key results can measure the predictive power of returns and stock market fluctuations in determining the level of economic activity of investors. Accurate measurement of these relationships helps investors predict stock market movements in the future and Develop, plan and implement their own investment strategies in each time horizon. In this research Maximal overlap discrete wavelet transform has been used to investigate the relationships between industries return fluctuations and stock main indices in different time horizons from 2011 to 2020 have been estimated. The results showed that the wavelet variance of the rate of return varies in different industries. The return of investment companies on various time scales is equal to the investment return of the banking industry. The variance of the total index is less on different time scales than the value of the cash index.