Cengiz Erol, Hasan F. Baklaci, Berna Aydoğan and Gökçe Tunç
The purpose of this paper is to attempt to compare the performance of Islamic banks against conventional banks in Turkey. This comparison is much more distinctive and significant…
Abstract
Purpose
The purpose of this paper is to attempt to compare the performance of Islamic banks against conventional banks in Turkey. This comparison is much more distinctive and significant in Turkey when compared to other countries, as Turkey stands as a model for the world in interest-free banking system.
Design/methodology/approach
The comparative performance analysis was conducted by means of logistic regression method during the period of 2001-2009. The CAMELS approach is utilized to assess the managerial and financial performance of banks.
Findings
The results signify that Islamic banks operating in Turkey perform better in profitability and asset management ratios compared to conventional banks but lag in sensitivity to market risk criterion. These findings might mainly be ascribed to the fact that these banks allow lower provisional losses compared to conventional banks and have some tax advantages.
Research limitations/implications
Utilizing a more recent and consistent data set, the analyses could be replicated to determine if the results are subject to any sample bias.
Practical implications
These finding reveal significant implications for potential entrants into Turkish banking sector particularly for foreign investors.
Social implications
The findings from this study may reinforce the awareness and confidence in participating banks in Turkey.
Originality/value
Turkey is particularly interesting to conduct this analysis because Turkey is a Muslim but secular country and both Islamic and conventional banks are subject to same set of banking regulations which are based on Western traditional banking system. Furthermore, to the knowledge, there is not a comprehensive study that compares the performance of conventional and Islamic banks in a Western banking system.
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Debmallya Chatterjee and Amol S. Dhaigude
This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance.
Abstract
Purpose
This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance.
Design/methodology/approach
The FMQD in evaluating banking performance are explored through the review of literature. The identified factors are modeled using integrated fuzzy cognitive map (FCM) and Matrices’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) approach. Scenario analysis is carried out on the proposed model to study the behavior in a dynamic setting.
Findings
The main finding of this study is the prioritization of FMQD in evaluating banking performance. The cohesive model obtained by FCM-MICMAC integrated approach demonstrates that the interlinked factors can be grouped into independent, autonomous, dependent and relay clusters. The results suggest that internal control system is the most influential factor, whereas the business per employee is the most sensitive one in modeling management quality.
Research limitations/implications
This study models the FMQD through expert opinions, and hence, individual bias may influence the results. This study can be further validated through statistical analysis.
Practical implications
The study suggests that practitioners may focus more on these select factors and their mutual interactions to enhance management quality for improving the performance of the banks. The study emphasizes that better clarity and efficient designing of internal processes are the key to management soundness.
Originality/value
This is the first study to explore and model FMQD in banking performance using FCM-MICMAC approach. Validation of the proposed model in a dynamic setting is also relatively new in the banking performance literature.
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A. Bouteska, Mohamad Kabir Hassan and M. Faisal Safa
This paper aims to use three proxy variables – initial public offerings, trading volume and business confidence index (BCI) to construct an investor sentiment index both for the…
Abstract
Purpose
This paper aims to use three proxy variables – initial public offerings, trading volume and business confidence index (BCI) to construct an investor sentiment index both for the USA and China, taking into account the challenging periods of the COVID-19 pandemic and the Russo-Ukrainian conflict.
Design/methodology/approach
Based on monthly data for a period from January 2009 to June 2022, this paper uses data of BCI, consumer confidence index (CCI), gross domestic product, trading volume and Fama and French (1993) factor data; linear regression of single and multifactor model; and EGARCH-M model for analyzing the effect of investor sentiment on stock market return and volatility, both in the USA and China.
Findings
The empirical results indicate the suitability of BCI over CCI as a measure of investor sentiment, both in the USA and China. The results indicate that investor sentiment has a significant positive effect on the excess returns in the stock market in both countries. Moreover, the effect of investor sentiment is higher in China than it is in the USA. Such an effect of investor sentiment is significant and fluctuates asymmetrically in the short run but loses its significance in the long run. Optimistic investor sentiment has a larger effect on the stock market volatility in the USA, while the pessimistic investor sentiment has a larger effect in the Chinese stock market.
Originality/value
This paper focuses on finding a more suitable proxy for investor sentiment from BCI or CCI. This paper also contributes by including both optimism and pessimism in explaining the stock return and volatility in both markets. The overall findings are important for understanding investor behavior in different market conditions.