Journal of Money & Economy
Volume:16 Issue: 1, Winter 2021

Money laundering is among the most common financial crimes that negatively affect countries' economies and hurt their social and political relations. With the increasing growth of e-banking and the increase in electronic financial transactions, the identification of money laundering methods and behaviors has become more complex; because money launderers, by accessing the Internet and using new technologies, find new ways to legalize their illegal income. Although many efforts have been made to identify suspected cases of money laundering and fight against this financial crime, little success has been achieved in this regard, especially in developing countries. Hence, this study tries to identify the risk factors involved in money laundering in banking transactions. To this end, multiple attribute decision-making methods, such as the Shannon entropy method, hierarchical analysis, and two-level fuzzy hierarchical analysis, have been used to assess and score the risk of various transactions in money laundering. The results indicated that the highest risk of money laundering was in the POS transactions.

This study investigates the effect of intra-organizational and macroeconomic factors on banking leverage in selected Iranian banks. For this purpose, after calculation of the Banking Leverage for each bank, by using Random-Coefficients Approach (Swamy model), the impact of explanatory variables during the period of 1999-2016 was examined separately by 10 selected Iranian public and private banks. Based on calculations, Melli, Saderat, Refah, and Tejarat Bank had the highest and Sanat-va-Madan, Eghtesad-Novin, and Sepah had the lowest level of banking leverage. Furthermore; the results of estimations show that "organizational" and "structural-variables" of each bank have different effects on their banking leverage. For example, "credit risk" has a positive and significant effect on bank leverage in "Tejarat", "Saderat", "Refah" and "Sanat-va-Madan" banks. The effect of "liquidity risk" is the same as "credit risk". In general, due to banks' dissimilar structures, organizational and structural variables hold a varying impact on their banking leverage.

This paper examines the hedging effectiveness of gold futures for the stock market in minimizing variance and downside risks, including value at risk and expected shortfall using data from the Iran emerging capital market during four different sub-periods from December 2008 to August 2018. We employ dynamic conditional correlation models including VARMA-BGARCH (DCC, ADCC, BEKK, and ABEKK) and copula-GARCH with different copula functions to estimate volatilities and conditional correlations between Iran gold futures contract return and Tehran stock exchange main index return. The empirical results reveal that the dynamic conditional correlations switch between positive and near-zero values over the period under study. These correlations are high and positive during the major national currency devaluation and are low near to zero during other times. Out-of-sample one-step-ahead forecasts based on rolling window analysis show that DCC and ADCC multivariate GARCH models outperform other models for variance reduction, while a more interesting finding is that the copula-GARCH model outperforms other models for downside risks reduction.

Structural change plays an important role in developing any economy, so understanding it is critical to make policies that increase total factor productivity. The structural change that leads to an efficient resource allocation after trade reforms is desirable; the key factor that can affect the relation of "structural change and trade liberalization" with productivity is the quality of institutions. In this study, we first use the principal component method to propose a multidimensional index for structural change and then apply the ARDL econometrics model to evaluate the effect of trade liberalization and structural changes on total factor productivity in Iran during 1991- 2018. The results show that structural changes increase the total factor productivity, and trade liberalization has a positive and significant effect on total factor productivity in the short term. Our results also indicate that there is no long-run relationship in this period.

Although gold is no longer a central cornerstone of the international monetary and financial system, it still attracts considerable attention from researchers and investors. Nowadays, many investors manage their risk with valuable assets such as gold. This paper examines the dynamic relationships between gold and stock markets in the Tehran Stock Exchange. We have applied the Markov switching method to study the role of gold as a hedge or safe haven for the Tehran Stock Exchange risk from 1998 to 2018. The high dependence and low dependence regimes used in the Markov switching model are based on empirical results that show two regimes for all markets under investigation: a low volatility regime and a high volatility regime. The study's findings show that gold can act as a strong hedge and cannot act as a safe haven for risk of The Tehran stock exchange.

Knowing and managing the concept of customer experience is the main factor in creating competitiveness for any organization. Moreover, without customer experience management, a business cannot specify appropriate strategies to maintain the current market and business sustainability. However, most of the existing studies have looked at this subject abstractly and have not provided a comprehensive model based on steps taken in the customer journey. This research aims to fill the gap by providing the body of knowledge with a comprehensive model for customer experience management, where the stepwise nature of the concept is maintained. Using a grounded theory (GT) strategy, 20 experts in the Iranian IT sector took part in this study. Data gathered using an interview protocol that was made based on reviewing the existing literature. Both reliability (Inter-coder rating) and validity (face and content validity) measures for the data gathering tool were obtained. Three coding approaches of grounded theory (open, axial, and selective coding) were applied to analyze the data. This study introduced a stepwise model of customer management experience through the customer journey steps. The model also contains the prerequisites conditions to realize the customer experience in the IT sector and reveals the contextual factors affecting the process and finally the consequences of applying the model.