فصلنامه پژوهش های پولی - بانکی
پیاپی 18 (زمستان 1392)

The fluctuations in the house price in some countries including Iran have been one of the most important challenges in house market and economy. The most important factors which follow the fluctuation and house price bubble are diversion in allocation of economic resources, changes in the behavior of producers and consumers and intensification of capital transfer in the assets market, which have made it so vital to identify and control it in the field of monetary policies. In this study, the real house prices over the period 1989 to 2009 using quarterly data and state space form is modeling. Using extracted bubble, factors affecting it are estimated by ordinary least squares method. The results from the estimation confirm the presence of a bubble in house price. These results indicate that part of the fluctuations in houses price is explained by house price bubble (non-fundamental forces in house price) and real liquidity and gross domestic product growth variables have significant and positive impact and stock price index has a negative effect on it.

Inflation rate is one of the most crucial macroeconomic variables and accurate real time forecast of it is of great importance to policy making institutions, especially central banks. One of the methods that have been proposed to increase the accuracy of forecasts is making use of information content of an extensive set of diverse variables using forecast combination methods. In this paper, some of the forecast combination techniques are implemented to forecast Iran’s inflation rate and then evaluated in real time. Our results show that firstly, simple combination methods have better performance compared to the combination methods that estimate the optimal weights. Secondly, ignoring the correlation between simple forecasts-when estimating the weights-will increase the accuracy of forecasts. Thirdly, the combination methods with optimal weights beat the methods with shrinking weights. Finally, the performance of the methods with shrinking weights is improved by increasing the shrinkage factor.

Having defined the “Shariah Supervision” concept and going over its operational models in the Islamic banks of others countries, this paper tries to come up with a suitable Shariah Supervision model for the Iranian banking system. The three-round Delphi technique is used to gather the views of the Islamic banking expert and the Binomial Test and the Friedman Test are used to analyze the collected information and ranking the characteristics of the suitable model. The results are threefold. First, in the three decades that the Usury-Free Banking Act has been in practice in Iran, the banking system has not been successful in conducting this law completely and the relevant Shariah Supervision has not been used neither in the central bank nor in the banks themselves. Second, among the different models of Shariah Supervision, the “maximum level of supervision model” is the best for Iranian banking system; third, the suitable model of Shariah Supervision should have some special features; however, the importance of different features is not equal. The findings of the paper might pave the way to conduct the usury-free banking act in a better manner and increase the level of Shariah Compliance in the Iranian banks operation.

The problem of lack of security in transactions is a relatively new challenge for developing e-banking in recent years. So, fraud detection has been one of the most important issues in financial institutions and specially banks. On the other hand, credit card banking is one of the main branches of e-banking. Although lots of researches have been done in the field of fraud detection, the trustful ways with high detection rate in credit card have been rarely investigated. Therefore, in this paper we concentrate on this narrow field. We applied credit card fraud detection by Artificial Immune System (called as AIS) algorithms and specially the dendritic cell algorithm (Called as DCA). It has the advantage of not having a training phase shortening the application process and low weight in computation improving detection speed. Furthermore, it is appropriate for data stream which is used in online fraud detection. The experimental results show that DCA is suitable enough for fraud detection in credit card based on 90% detection rate. In addition, this algorithm decreases the FP rate by applying safe signal.

This paper studies whether compliance with the Basel Core Principles for Effective Banking Supervision improves bank soundness in Iranian banking system. We find a significant and positive relationship between bank soundness and compliance with principles. This relationship is robust to controlling for broad indexes of institutional quality, macroeconomic variables, sovereign ratings, as well as reverse causality. Measuring soundness through Z-scores that show the Basel Core Principles for Effective Banking Supervision (BCPs) improves bank soundness similar results. These findings emphasize the importance of transparency in making supervisory processes effective and strengthening market discipline.

In this study, the Relation of money innovations and money demand in Iran in the form of time series between 1959 and 2010 by ARDL method has been tested. Financial Innovations is a broad concept in Money Substitution whose main part is formed in bank section. Here, focusing on bank part (section), the effect of financial innovations on money demand is examined. Results show that in a given period in spite of Financial Innovations money demand is stable. Here are long run relations and consequently short – run dynamic adjustment toward equilibrium between money demand and inflation rate variable, GDP and Financial Innovations. Financial Innovations has negative effect on money demand in short and long run as a focused variable of the current study. The speed of model adjustment toward long–run one in both models is low. Also short-run elasticity of Financial Innovations is more than long run one.

Unbundling of institutions has been ignored while investigating the effects of resource curse on their quality. Meanwhile, the effects of institutions on economic performance and the process of their vulnerability to resources can differ based on their performance and roles. This study aims at Unbundling of institutions and investigation of the effects of their dependency on natural resources on their quality. Three factors of development level before dependency, geographical situation, and colonialism has also been seen as effective in the quality of institutions. Results reveal that dependency on oil and minerals reduces the quality of political and economic institutions. Findings support the theory that dependency on resources can weaken the quality of institutions and consequently lead to resource curse in resource-rich countries.